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Bachelor Medizinische Informatik

Fast facts

  • Department

    Informatik

  • Stand/version

    2026

  • Standard period of study (semester)

    6

  • ECTS

    0

Study plan

  • Compulsory elective modules 2. Semester

  • Compulsory elective modules 3. Semester

  • Compulsory elective modules 4. Semester

  • Compulsory elective modules 6. Semester

Module overview

1. Semester of study

Algorithmen und Programmierung
  • PF
  • 8 SWS
  • 5 ECTS

  • Number

    41011

  • Language(s)

    de

  • Duration (semester)

    1

  • Contact time

    75 h

  • Self-study

    75 h


Learning outcomes/competences

Learning outcomes / competences
After successfully completing this module, students will be able to:
Knowledge and understanding:
  • Explain principles, methods, concepts and notations of "programming in miniature"
  • .
  • Explain basic elements of imperative programs such as data types and operators, expressions and methods, control structures and fields.
  • explain the principle of recursion and reproduce it in given programs with recursion.explain the concept of runtime complexity and represent the runtime of given algorithms or programs using O-notation.describe different algorithms for searching for values in sorted and unsorted value sets.describe different algorithms for sorting value sets. Use, application and generation of knowledge:
    • read programs written in a given programming language and understand and predict their execution
    • .
    • use the principles, concepts, notations and basic elements learned in programs.
    • apply rules for the formation of expressions using examples.
    • recognize and correct syntactic and semantic errors in programs. 
    • understand problem descriptions and construct example inputs and outputs for the problem
    • to independently design a solution to a given problem in the form of an algorithm.
    • implement a given algorithm in a programming language 
    • create a program in a development environment step by step, test it, and detect and correct errors.
    • analyze different algorithms for solving a problem class and compare them in terms of their runtime.to program search algorithms
    • program sorting algorithms and compare their runtime complexity
    Communication and cooperation:
    • understand and describe a problem solution with the help of examples
    • .
    • formulate a solution to a problem and in the form of an imperative algorithm
    • .
    • develop small programs in teams to solve small problems and communicate about errors and possible solutions.
    • Scientific self-image / professionalism:
      • Analyze the quality of programs
      • .

Contents

  • Computers, computer science
  • Java introduction
  • Data types and operators
  • Expressions, methods
  • Control structures
  • Algorithms
  • Fields
  • Recursion
  • Complexity
  • Search
  • Sort

Teaching methods

  • Lecture in interaction with the students, with blackboard writing and projection
  • Solving practical exercises in individual or team work
  • Processing programming tasks on the computer in individual or team work
  • Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

  • written written examination
  • study achievements during the semester (bonus points)

Requirements for the awarding of credit points

  • passed written exam

Applicability of the module (in other degree programs)

  • Bachelor of Business Informatics
  • Bachelor of Software and Systems Engineering (dual)
  • Bachelor of Computer Science
  • Bachelor's degree in Medical Informatics
  • Bachelor of Medical Informatics Dual
  • Bachelor of Computer Science Dual

Literature

  • D. Ratz, D. Schulmeister-Zimolong, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 9. Auflage, Hanser, 2024
  • C. Ullenboom, Java ist auch eine Insel, 17. Auflage, Galileo Press, 2023
  • A. Solymosi, U. Grude, Grundkurs Algorithmen und Datenstrukturen in JAVA, Springer Vieweg 2017
  • R. Sedgewick, K. Wayne, Algorithmen: Algorithmen und Datenstrukturen, 4. Auflage, Pearson Studium 2014
  •  H. Balzert, Java: Objektorientiert programmieren, 3. Auflage, Springer Campus, 2017

Algorithmen und Programmierung – Projektwoche
  • PF
  • 2 SWS
  • 2.5 ECTS

  • Number

    41012

  • Language(s)

    de

  • Duration (semester)

    1

  • Contact time

    30h

  • Self-study

    45h


Learning outcomes/competences

After completing the course, students will have mastered the most important principles of object-oriented programming on a small scale and have a basic understanding of the structure and functioning of computers.

Technical and methodological competence:
You will acquire the formal competence to understand the principles, methods, concepts and notations of programming on a small scale, to classify them in different contexts and to use them in object-oriented programs. This also includes identifying the algorithmic core of a simple problem and designing an imperative algorithm.
They acquire basic analysis skills that enable them to implement simple object-oriented models in UML notation in the Java programming language. This competence also includes the ability to familiarize themselves independently with applications (such as development environments, learning platforms).
You have the implementation skills to develop and analyze object-oriented programs in Java.

Interdisciplinary methodological competence:
Graduates are familiar with historical developments in computer science. They are aware of the security problems associated with the use of information processing systems. They have key qualifications such as the ability to use new media. They have experience in solving application problems in a team.

Social skills:
Students acquire communicative competence in order to present their ideas and proposed solutions convincingly in writing or orally, even if their counterparts are not familiar with the computer science way of speaking and thinking.

Contents

  • Fundamental concepts of computer science
  • Procedures for the step-by-step development of programs
  • Elements of imperative programming: data types, control structures, operations
  • Elements of object-oriented programming: objects, classes, interfaces, inheritance, polymorphism
  • Description methods of object-oriented programming, e.g. UML

Teaching methods

  • Lecture in interaction with the students, with blackboard writing and projection
  • Solving practical exercises in individual or team work
  • Processing programming tasks on the computer in individual or team work
  • Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

Participation requirements

See the respective valid examination regulations (BPO/MPO) of the study program.

Forms of examination

  • written written examination
  • study achievements during the semester (bonus points)
  • Participation in project week (ungraded)

Requirements for the awarding of credit points

  • passed written exam
  • successful participation in project week (2 SWS internship)
  • participation in at least 80% of the attendance dates in the project week

Applicability of the module (in other degree programs)

  • Bachelor of Business Informatics
  • Bachelor of Software and Systems Engineering (dual)
  • Bachelor of Computer Science
  • Bachelor's degree in Medical Informatics
  • Bachelor of Medical Informatics Dual
  • Bachelor of Computer Science Dual

Literature

  • H. Balzert, Java: Der Einstieg in die Programmierung, 4. Auflage, Springer Campus, 2013
  • H. Balzert, Java: Objektorientiert programmieren, 3. Auflage, Springer Campus, 2017
  • H. P. Gumm, M. Sommer, Grundlagen der Informatik: Programmierung, Algorithmen und Datenstrukturen, Oldenbourg, 2016
  • S. Goll, C. Heinisch, Java als erste Programmiersprache, 8. Auflage, Springer Vieweg, 2016
  • D. Ratz, J. Scheffler, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 7. Auflage, Hanser, 2014
  • C. Ullenboom, Java ist auch eine Insel, 12. Auflage, Galileo Press, 2016 (siehe auch http://openbook.galileocomputing.de/javainsel/)

 

Projektwoche

Das Modul beinhaltet eine Projektwoche (I9PB-41012, 2 SWS). Die Klausurarbeit und die Projektwoche können unabhänig voneinander abgelegt werden. Für das Bestehen des Moduls ist neben einer Klausur die erfolgreiche Teilnahme an der Projektwoche erforderlich. Die Note des Moduls wird ausschließlich über die Klausurarbeit definiert. Die Projektwoche wird als 5-Tägige Blockveranstaltung im Anschluss an die Vorlesung angeboten.

Datenbanken
  • PF
  • 5 SWS
  • 5 ECTS

  • Number

    43052

  • Language(s)

    de

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h


Learning outcomes/competences

Knowledge and understanding:

  • Name principles, concepts, methods of database systems and the database language SQL
  • Explain aspects of integrity in database systems and for database implementations
  • Deduce database schemas from data models
Deployment, application and generation of knowledge:
  • Using modern modeling tools
  • Choosing constructs for data modeling
  • Designing and creating relational data models (SQL)
  • Creating simple to complex database queries
Communication and cooperation:
  • Discuss the pros and cons of data models, databases and queries with experts
  • Present data models to experts and non-experts
Scientific self-image / professionalism:
  • Name the possibilities and limitations of relational databases
  • Explain the meaning of the semantics of data

Contents

A more complex data model and its implementation, including a database for transfusion documentation, serves as the basis for the course. The data model contains essential aspects that are used in many medical applications, such as the mapping of an organization consisting of organizational units and employees (here doctors, nurses, etc.), the management of materials (here blood products), medical measures and their results (here transfusion anamnesis and transfusion as well as checks after transfusions) and status information on transfusions and blood products. The database represents a small hospital with corresponding patients and their transfusions. Concepts and content conveyed are repeatedly reflected using this database as an example.

  • Basic concepts of database systems: Layer model, encapsulation, data independence, data dictionary, consistency, integrity, synchronization, transaction concept, data protection and security
  • Introduction to database models and their creation, also derived from class models
  • Special properties of the relational model: paradigm, structures and operations
  • The SQL language standard: data types, structure definitions, integrity aspects, database updates (insert, update, delete), structure of the select statement, simple select statement, functions, data grouping, group functions, subselects, compound operations, views
  • Applications in the practical course and exercises based on MySQL
  • Triggers, DB procedures
  • The exercises are based on the above-mentioned database; as part of the practical course, students have to design and implement a model themselves based on a given small problem description, enter test data and carry out queries

    .

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work (exercises during the semester)
    • Processing programming tasks on the computer in individual or team work (practical courses during the semester)

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written written exam (90 minutes)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • R. Elmasri, S. Navathe, Grundlagen von Datenbanksystemen, 2009
    • Kemper, A. Eickler, Datenbanksysteme (Eine Einführung), 2015
    • Beighley, L., SQL von Kopf bis Fuß, O'Reilly, 2008.
    • Saake, G., Sattler, K., Heuer A., Datenbanken - Konzepte und Sprachen, 6. Auflage, mitp, 2018.

    Mathematik für Informatik 1
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      41064

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    • Students master basic mathematical concepts of computer science and their methods such as set theory, relations, propositional logic, complex numbers as well as groups and solids.
    • Students who have completed the module have mastered basic and advanced concepts and methods from linear algebra and are able to apply these methods with reference to their practical applications to solve typical tasks in computer science.
    • The graduates demonstrate a confident handling of the concepts and methods of vector and matrix calculus and their geometric interpretation, setting up and solving linear systems of equations as well as dealing with straight lines and planes.

    Interdisciplinary methodological skills and self-competence:

    • Graduates of the module are able to solve computer science problems by setting up and calculating the corresponding mathematical models (for example by setting up and solving linear systems of equations). They demonstrate confidence in the appropriate selection of problem-specific solution methods and their application.
    • The students are able to recognize the mathematical structures they have learned in other areas of computer science and to transfer the methods they have learned to these areas.

      Social skills:

      • The participants understand the relevance of the content taught to their field of study and are able to communicate this relevance adequately.

    Contents

    The event includes the following topics:

    • Basics of mathematics for computer scientists: Introduction to set theory, cardinality of sets, relations, basics of propositional logic, complex numbers, groups and solids.
    • Vectors and vector calculus: notation and interpretation, operations on vectors and their properties (addition, scalar multiplication, scalar product, cross product), vector spaces, length of vectors, collinearity, linear dependence and independence, concepts of dimension and basis, angles between vectors.
    • Lines and planes: Representation in linear algebra, applications, positional relationships between points / straight line / planes
    • Matrices: Notation and interpretation, operations on matrices and their properties (transposing matrices, addition, scalar multiplication, matrix multiplication), Gaussian algorithm, determinants, inverse matrices and their calculation
    • Linear systems of equations: motivation and applications, matrix-vector form of linear systems of equations, Gaussian algorithm for solving linear systems of equations, homogeneous and inhomogeneous linear systems of equations and their relationships, rank of a matrix and relation to the solution set of linear systems of equations
    • Eigenvalues and basic transformations

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Skript zur Vorlesung,
    • G. Teschl und S. Teschl, Mathematik für Informatiker 1, 3. Auflage, Springer Verlag (2008) - im Intranet der FH elektronisch verfügbar.
    • G. Teschl und S. Teschl, Mathematik für Informatiker 2, 2. Auflage, Springer Verlag (2007) - im Intranet der FH elektronisch verfügbar.
    • G. Fischer, Lineare Algebra, Vieweg, Braunschweig/Wiesbaden, 12. Auflage (2000).
    • Preuß, W., Wenisch, G., Lehr- und Übungsbuch Mathematik für Informatiker.

    Medizinische Grundlagen
    • PF
    • 5 SWS
    • 5 ECTS

    • Number

      42412

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      75 h

    • Self-study

      75 h


    Learning outcomes/competences

    Subject and methodological competence:
    This module teaches students the fundamentals of medicine that are essential for their further studies and professional career, whereby the principles of medical thinking and acting as well as the organization of treatment processes based on the division of labour also represent an essential aspect. These aspects are always considered against the background of process-related IT support. With a view to the two specializations in later studies, the basics are aligned with this. While profound knowledge of medical action, the organization of medical treatment processes and medical anatomy, terminology and the range of measures (the latter for understanding medical classification systems) is particularly important for the focus on informatics in healthcare, knowledge of anatomy and neurophysiology as well as special diagnostic procedures is particularly important for medical technology.
    Expert knowledge:

    • Medical basics of anatomy and neurophysiology
    • Medical Terminology
    • Methodological aspects of medical practice
    • Economically significant diseases and their diagnostic and therapeutic concepts
    Professional field orientation:
    • Knowledge of the most important processes and decision-making mechanisms in medicine
    • Dialogue skills with medical professionals in the context of requirements analyses

    Contents

    This module covers the basics of human medicine with a view to anatomy, physiology and pathology as well as corresponding medical terminology. Furthermore, health models and methodological aspects of medical practice are addressed.
    The following content is covered in detail:

    • Conceptions of health and illness, health models
    • Principle aspects of medical practice
      • Phase concept from prevention to rehabilitation
      • Selected aspects of diagnostics and diagnostic measures as well as therapeutics and therapeutic measures
      • Pathodynamics, interventions and their significance
    • Basics of human medicine
      • Anatomy
      • Physiology
      • Pathology
      • Terminology
      • Nosology, diagnostics and therapeutic concepts of selected diseases

    Teaching methods

    • Seminar-style lecture, with blackboard writing and projection
    • Processing of exercises during the lecture, possibly on the computer in individual or team work
    • Active, self-directed learning through the use of electronic learning materials

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper, 60 - 90 minutes

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Deschka Marc: Lernkarten Grundwortschatz Medizin - 324 Lernkarten zum Einstieg in die medizinische Fachsprache: Fachbegriffe, Fremdwörter & Terminologie. Bibliomed 2011.
    • Faller A., Schünke M.: Der Körper des Menschen. 14. Ausgabe. Thieme Stuttgart 2004.
    • Groß R., Löffler M., Gontard S.: Prinzipien der Medizin. Springer Berlin 1997
    • Grün A.H., Vierbahn R.: Medizin für Nichtmediziner. Ku-Verlag 2007.

    Technisches Englisch
    • PF
    • 2 SWS
    • 2.5 ECTS

    • Number

      41102

    • Language(s)

      en

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    After successful completion of the module students will be able to:

    Knowledge and understanding

    •  name and explain key technical vocabulary from IT and technology .
    • describe technical objects, systems and processes precisely in Englishhe describe.

    Use, application and generation of knowledge

    • structure technical content appropriately for the target group(introduction - main part - conclusion) and  transfer it into an understandable presentation .
    • Suitable visualizations (e.g. diagrams/tables) to support technical statements  statements use.
    •  Summarize technical information concisely together (e.g. abstract/handout/slide-text) and  put them into presentation materials integrate.

    Communication and cooperation

    • present technical content correctly and comprehensibly in English .
    • an English-language technical discussion lead by asking questions, arguing and giving feedback.

    Scientific self-image / Professionalism

    • Fundamental principles of scientific work in English apply by citing and citing sources correctly.
    • the own linguistic and technical presentation reflect and  further develop this with the help of feedback develop.

    Contents

    • Basics of technical English: Technical vocabulary, typical formulations, description of technical facts.
    • Presentation techniques: Structure/outline, linguistic means, presentation phrases, use of visual aids. visual aids
    • .
    • Scientific work: Source work, citation techniques, precise summaries of technical content. content.
    • Discussion techniques: Questions/answers, argumentation, feedback, role plays/exercises on IT topics.
    • Practical application: Presentations on technical IT topics during the semester
    .

    Teaching methods

    • Seminar-style teaching in English language with activating phases.
    • Oral and written exercises on technical technical description and terminology.
    • Presentation workshops (preparation, implementation, feedback).
    • Discussions/role-playing games on current IT topics.
    • Independent research and development of presentation content. presentation content.

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    R (presentation / presentation), ungraded (pass / fail)

    Competence-oriented Description of the examination:
    With the presentation, students demonstrate that they can present technical content in a technically correct, structured and target group-oriented manner in English and can answer questions in a short technical discussion.

    • Duration: 10-15 minutes presentation + subsequent Q&A session
    • Evaluation criteria (pass/fail) passed): Professionalism, comprehensibility, linguistic accuracy, presentation technique accuracy, presentation technique

    Requirements for the awarding of credit points

    • Participation in the placement test before the semester.
    • Passed semester presentation (10-15 minutes) with Q&A session.
    • Minimum attendance: At least 80 % of the appointments (usually corresponds to max. 20 % missing appointments); required, as learning objectives can only be achieved through continuous practice, presentation and discussion. If the minimum attendance is not met without excuse, the preliminary examination work is deemed not to have been completed. As a result, the module will be graded as "failed" (NB).

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    Williams, E., Kleinschroth, R., Courtney, B. (2025). "Matters Technik - IT Matters 3rd Edition - Revised: B1-C1 - Englisch für technische Ausbildungsberufe". Cornelsen Verlag. ISBN-13: 978-3-06-452538-2

    Lern- u. Arbeitstechniken
    • WP
    • 2 SWS
    • 2.5 ECTS

    • Number

      411031

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    Interdisciplinary methodological competence:

    • After successful participation in the module courses, students are able to understand standards and procedures in the field of learning and working techniques (including time and self-management, learning theory, communication and effective collaboration as well as creativity techniques) and apply them to their studies across disciplines.
    Self-competence:
    • After successfully completing the module courses, students will be able to apply learning methods, communication and presentation techniques, creativity and problem-solving techniques, time and self-management methods and the basics of academic work to their studies and career.

    Social skills:

    • After successful participation in the module courses, students are able to apply techniques of effective cooperation and problem-solving techniques in groups.

    Contents

    The course includes modules on the following topics:

    • Time management
    • Self-management
    • Motivation
    • Burnout
    • Creativity
    • Problem solving techniques
    • Effective collaboration
    • Learning types
    • Basics of scientific work
    • Mentoring discussions (include questions of study choice, study organization, individual time and learning planning, dealing with difficult situations and preparation for internships)

    Teaching methods

    Seminar-style teaching with flipchart, smartboard or projection

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Homework at the end of the semester [100%] (pass or fail)
    Attendance in at least 80% of the modules of the course

    Reason for the attendance obligation

    The course should enable students to apply various learning, work, communication and self-management techniques in their studies and everyday professional life. Due to their nature, learning these skills requires both intensive cooperation with and personal guidance from the respective lecturers, as well as a large amount of practical work in the group under active supervision by the lecturers. In order to achieve these goals, a minimum attendance requirement is necessary in this course.

    Requirements for the awarding of credit points

    • Passed term paper
    • Participation in at least 80% of the modules of the course
    • Participation in the mentoring program
    Reason for the participation obligation

    The course should enable students to apply various learning, work, communication and self-management techniques in their studies and everyday professional life. Due to their nature, learning these skills requires both intensive cooperation with and personal guidance from the respective lecturers, as well as a variety of practical work in the group under active supervision by the lecturers. In order to achieve these goals, a minimum attendance requirement is necessary in this course.

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Friedrich Rost; Lern- und Arbeitstechniken für das Studium; Vs Verlag 6. Auflage 2010; ISBN-13: 978-3531172934
     

     

    Studium Generale
    • WP
    • 2 SWS
    • 2.5 ECTS

    • Number

      411033

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    In this module, students can choose from a selection of cross-university courses. The competencies are defined by the respective course.

    Contents

    In this module, you can choose from a selection of cross-university courses. The content is defined by the respective course.

    Teaching methods

    In this module, students can choose from a selection of cross-university courses. The forms of teaching are defined by the respective course.

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    In this module, students can choose from a selection of cross-university courses. The forms of examination are defined by the respective course.

    Requirements for the awarding of credit points

    In this module, students can choose from a selection of cross-university courses. The prerequisites are defined by the respective course.

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    Williams, E., Kleinschroth, R., Courtney, B. (2025). "Matters Technik - IT Matters 3rd Edition - Revised: B1-C1 - Englisch für technische Ausbildungsberufe". Cornelsen Verlag. ISBN-13: 978-3-06-452538-2

    2. Semester of study

    Grundlagen der Medizinischen Informatik
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      42401

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Subject and methodological competence:
    After completing the module, students will be able to gain an overall overview of the application-related computer science subject "Medical Informatics", establish connections between the various application areas and sub-areas and be able to classify the topics in terms of subject and profession. They know the necessary basics of the two main areas of specialization. Students are familiar with all the main IT applications of medical informatics and the associated basics.
    Among other things, students will be able to

    • Name the goals, tasks and main areas of application of medical informatics
    • explain the organization and financing of the German healthcare system
    • Explain the objectives and benefits of medical IT applications
    • explain the basic principles of medical information systems and use a medical practice information system and a hospital information system as a user
    • med. model procedures/processes and explain the importance of process support through IT
    • analyze medical forms and other documentation templates and standardize them with a view to IT implementation
    • classify medical classification systems and select and apply them for documentation drafts
    • design medical documentation for specific areas of application
    • to explain which medical signals and imaging procedures exist and how these can be transferred to computer systems and processed there
    • Describe the objectives and procedures of clinical studies and describe the use of IT for this purpose
    Professional field orientation:
    • Knowledge of the possible applications of IT in healthcare and the associated skills required by medical informatics specialists
    • Knowing the different organizational forms and requirements for IT in healthcare facilities
    • Know many important classification systems and technical terms

    Contents

    • Definitions of MI / orientations and sub-areas of MI / possibilities for supporting medicine through informatics
    • Healthcare system in Germany, relevant laws, especially SGB, financing principles
    • Important institutions in the healthcare system and their tasks
    • Peculiarities of the division of labour in the organization of treatment processes in the outpatient and inpatient sector
    • Peculiarities of medical data/information and medical information systems as well as data protection aspects
    • Conventional medical documentation, setting up archives, documentation and retention obligations
    • Standardization of documents and documentation objectives, intended use, methodology
    • Necessity, structure and examples of medical filing systems
    • Information sources and knowledge bases in medicine
    • Operational information systems in healthcare; especially hospital and medical practice information systems
    • Telematics and telemedicine applications using examples
    • Biomedical signals and principles of signal processing
    • Imaging techniques in medicine and principles of image processing
    • Medical biometrics: therapeutic studies, diagnostic tests, study planning and study phases
    • Epidemiology: basic concepts, measures, methods
    • Teaching and learning systems, computers in medical education and patient communication

    Teaching methods

    • Seminar-style lecture, with blackboard writing and projection
    • Processing exercises during the lecture, possibly on the computer in individual or team work
    • Active, self-directed learning through the use of electronic learning materials
    • Excursion

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam, 60 - 90 minutes

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Baas, J. (2020). Digitale Gesundheit in Europa: menschlich, vernetzt, nachhaltig. Medizinisch Wissenschaftliche Verlagsgesellschaft.
    • Bachmann, W. (2009). Praxishandbuch IT im Gesundheitswesen: Erfolgreich einführen, entwickeln, anwenden und betreiben. Hanser Verlag.
    • Dugas, M. (2017). Medizininformatik. Springer Berlin Heidelberg.
    • Haas, P.: Medizinische Informationssysteme und Elektronische Krankenakten, Springer 2004.
    • Jehle, R., Czeschik, J. C., Freund, T., & Wellnhofer, E. (Eds.). (2015). Medizinische informatik kompakt: Ein Kompendium für mediziner, informatiker, qualitätsmanager und epidemiologen. Walter de Gruyter GmbH & Co KG.
    • Johner, C., Hölzer-Klüpfel, M., & Wittorf, S. (2020). Basiswissen medizinische Software: Aus-und Weiterbildung zum certified professional for medical software. dpunkt. verlag.
    • Leiner, F. (2012). Medizinische Dokumentation: Grundlagen einer qualitätsgesicherten integrierten Krankenversorgung; Lehrbuch und Leitfaden; mit 24 Tabellen. Schattauer Verlag.
    • Marx, G. (2021). Telemedizin: Grundlagen und praktische Anwendung in stationären und ambulanten Einrichtungen. Springer.
    • Schlegel, W., Karger, C. P., & Jäkel, O. (Eds.). (2018). Medizinische Physik: Grundlagen–Bildgebung–Therapie–Technik. Springer-Verlag.
    • Simon, M. (2021). Das Gesundheitssystem in Deutschland: Eine Einführung in Struktur und Funktionsweise. Hogrefe AG.
    • Krankenhausinformationssystem M-KIS der Meierhofer AG (steht im Labor zur Verfügung) mit entsprechenden Handbüchern

    Informationssicherheit für die Medizin
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      46815

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    The students are able to

    • define, differentiate and explain basic information security terminology.
    • understand the central importance of standardization in information security and map it methodically.to independently view and analyze information about vulnerabilities and threats and make informed decisions based on this information.explain and apply organizational and technical security measures.

    Contents

    • Terminology
      • IT security, information security, difference between security and safety
      • Asset
      • Protection target (CIA and authentication)
      • Vulnerability, vulnerability, threat, attack, attacker types
      • Risk
      • Security measure
    • Security guidelines, human factor, security awareness
    • Legal framework, European General Data Protection Regulation
    • Standards and best practices
      • ISO/IEC 27000 series
      • Common Criteria
      • IT baseline protection
      • OWASP
    • Applied cryptography
      • Symmetric encryption (basics, AES, block modes, padding, pitfalls)
      • Hash functions (types of attack, SHA-2 family, SHA-3 family), MAC
      • Asymmetric cryptography (basics, DH, RSA, ECC, padding, pitfalls, digital shelf marks, certificates)
    • Access control
      • Basics (DAC, MAC, RBAC, Deny by Default, Least Privilege)
      • Advanced models (ABAC, ReBAC), modeling
    • Authentication
      • Basics of authentication (types, MFA, entropy)
      • Password-based authentication (Linux password databases, types of attacks, Salt, Argon2, NIST 800-63B)
    • Basics of software development and information security
      • Best practices (OWASP Top 10, SAMM, ASVS, Testing Guide)

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science Dual

    Literature

    • R. Anderson: Security Engineering: A Guide to Building Dependable Distributed Systems, 3. Auflage, John Wiley & Sons Inc., 2020
    • C. Eckert: IT Sicherheit (Konzepte, Verfahren, Protokolle), 11. Auflage, De Gruyter Oldenbourg, 2023
    • ISO/IEC 27000: Information technology Security techniques Information security management systems Overview and vocabulary, 2018
    • K. Schmeh: Kryptografie Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016

    Mathematik für Informatik 2
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      41063

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Students know the concept of function and can use it confidently. Principles of proof, especially complete induction, are understood and can be applied. Limit values of sequences and series, in particular Taylor series, can be determined. Students can differentiate and integrate functions and use this knowledge effectively in applications.

    Technical and methodological competence:
    Students have in-depth knowledge of the possible applications of differential and integral calculus: solution patterns are familiar; mathematical methods can be transferred to other problems.

    Interdisciplinary methodological competence:
    Students recognize that mathematical methods can be used to describe properties of medical informatics systems and analyze their behavior.

    Self-competence:
    Students can present ideas and proposed solutions orally and in writing. The independent presentation of solutions contributes to the development of self-confidence / professional competence. The development of strategies for acquiring knowledge and skills is supported by the combination of lectures, self-study and intensive practice phases with continuous feedback.

    Social skills:
    Cooperation and teamwork skills are trained during the practice phases. Students can argue in discussions in a goal-oriented manner and deal with criticism objectively. Existing misunderstandings between discussion partners are recognized and reduced.

    Orientation to the professional field:
    Communication with cooperation partners from technology-specific specialist areas/departments is made easier if the relevant language schemes have been familiarized with during mathematics training.

    Contents

    • Number ranges, complete induction
    • Functions: Polynomials (esp. interpolation polynomials), rational functions, exponential function, trigonometric and hyperbolic functions and their inverse functions as well as other elementary functions
    • Convergence of sequences and series, Landau symbolism
    • Limit values and continuity of functions, calculation of zeros of functions
    • Differentiability of functions; one- and multi-dimensional differential calculus
    • Rule of de l'Hospital
    • Taylor series expansion, approximation of functions by polynomials
    • Local and global extrema of functions in one or more variables
    • Integration of continuous functions in one variable (root function, integration techniques)

     

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Vorlesungskript
    • Forster, O.; Analysis 1; Vieweg,+Teubner; Wiesbaden; 12. Auflage; 2016
    • Hartmann P.; Mathematik für Informatiker; Vieweg+Teubner; Wiesbaden; 5. Auflage; 2012
    • Heuser, H.: Analysis 1, Wiesbaden, Vieweg-Teubner, 2009, 17. Auflage.
    • Heuser, H.: Analysis 2, Wiesbaden, Vieweg-Teubner, 2008, 14. Auflage.
    • Teschl G. und Teschl S.; Mathematik für Informatiker, Band 2 Analysis und Statistik; Springer; Heidelberg; 4. Auflage; 2013

    Mathematik für Informatik 3
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      42073

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Acquisition of basic knowledge of applied statistics and the ability to select and apply descriptive and inductive statistical methods to solve problems of practical relevance.

    Technical and methodological competence:

    • Acquisition of methodological basics of descriptive and inferential statistics
    • Describing essential structures in data by selecting suitable descriptive means
    • Converting problems into random variables and suitable distribution assumptions
    • Drawing inferences from samples to populations using parameter and interval estimation
    • Formulation of test problems and independent implementation of hypothesis tests
    • First experience with the computer-aided analysis of data

    Interdisciplinary methodological competence:

    • Supporting decision-making processes through descriptive data analysis and statistically sound statements
    • Transferring estimation and test procedures to problems in computer science
    • Applying statistical methods in connection with the evaluation of databases
    • Simulation of stochastic processes with the help of theoretical distributions
    • Derivation of forecasts using statistical estimation methods

    Contents

    • Empirical frequency distributions and graphical representations
    • Location measures, measures of dispersion and box plots
    • Measures of correlation and exploratory regression
    • Concept of probability, random events, Laplace model
    • Combinatorics
    • Conditional probability, independence of events, Bayes' theorem
    • Distribution and parameters of discrete random variables
    • Equal distribution, binomial distribution, hypergeometric distribution
    • Distribution and parameters of continuous random variables
    • Equal distribution, normal distribution, central limit theorem
    • Point estimators and their properties
    • Confidence intervals for expected value and proportion value
    • Testing hypotheses, binomial test, Gaussian test, t-test
    • Independent computer-aided analysis of data sets, e.g. in Excel, Python or R

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Processing programming tasks on the computer in individual or team work
    • Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Vorlesungsskript
    • Fahrmeir et al.; Statistik: Der Weg zur Datenanalyse; Springer; Berlin Heidelberg; 8. Auflage; 2016

    Objektorientierte Programmierung und Datenstrukturen
    • PF
    • 5 SWS
    • 5 ECTS

    • Number

      42012

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      75 h

    • Self-study

      75 h


    Learning outcomes/competences

    After successfully completing this module, students will be able to:

    Knowledge and understanding:

    • Explain the concepts of objects, classes, associations, and inheritance.
    • Describe the principles of interfaces and polymorphism.
    • Interpret UML class diagrams and object diagrams.
    • Explain the properties and functionality of lists, binary trees, AVL trees, B-trees, uand hashing.
    • Explain key concepts of graphs
    Use, application and generation of knowledge:
    • Implement objects and classes in an object-oriented programming language.
    • Implement UML class diagrams in an object-oriented language.
    • Apply and implement algorithms for efficient use of lists, trees and hashing.
    • Use given algorithms and data structures, such as collections in Java, to solve problems
    • Apply simple graph algorithms such as depth-first and breadth-first search, topological sorting, minimum spanning trees and shortest paths
    Communication and cooperation:
    • Develop smaller object-oriented software projects in teams.
    • Document and present program code and concepts to fellow students and instructors in an understandable way.
    Scientific self-image / professionalism:
    • Analyze simple algorithms and software structures for efficiency.
    • Reflect on the relevance of algorithms and data structures for software development.
    • Apply the principles of object-oriented programming systematically.

     

    Contents

    • Object-oriented concepts: objects, classes, associations, inheritance, interfaces, polymorphism
    • UML: Class diagrams and object diagrams
    • Data structures: lists, binary trees, AVL trees, B-trees, hashing
    • Graphs and simple graph algorithms (e.g. depth-first search, breadth-first search, topological sorting, minimum spanning trees, shortest paths)
    • Practical implementation in an object-oriented programming language (e.g. Java)

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Internship accompanying the lecture
    • Group work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science 
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • D. Ratz, D. Schulmeister-Zimolong, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 9. Auflage, Hanser, 2024
    • C. Ullenboom, Java ist auch eine Insel, 17. Auflage, Galileo Press, 2023
    • A. Solymosi, U. Grude, Grundkurs Algorithmen und Datenstrukturen in JAVA, Springer Vieweg 2017
    • R. Sedgewick, K. Wayne, Algorithmen: Algorithmen und Datenstrukturen, 4. Auflage, Pearson Studium 2014

    Objektorientierte Programmierung und Datenstrukturen – Projektwoche
    • PF
    • 2 SWS
    • 2.5 ECTS

    • Number

      42013

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30h

    • Self-study

      45h


    Learning outcomes/competences

    After successfully completing this module, students will be able to

    Knowledge and Understanding
    • Locate the theoretical concepts of object orientation (encapsulation, inheritance, polymorphism) in the context of a more complex application architecture.
    • Weigh up the advantages and disadvantages of different data structures (lists, sets, maps, trees) for specific use cases.
    • Understand the structure and life cycle of a complete console application.

    Use, apply and generate knowledge

    • Design and implement an executable console application independently based on a textual task.
    • Select and correctly apply suitable standard data structures for the efficient storage and processing of data
    • Write robust code that catches input errors and accounts for edge cases.
    • Use development tools (IDE, debugger) routinely to systematically find and fix logical errors in the program flow.  

    Communication and cooperation

    • Defining work packages in small groups (teams),
    • coordinating interfaces between program components and coordinating the integration of subcomponents.
    • Resolve conflicts and discuss solutions constructively when working together on source code
    • To justify own implementation decisions to team members in a professional manner.

    Scientific self-image / professionalism

    • To realistically estimate time resources within the framework of a fixed deadline (5-day block) and to adapt project management accordingly (timeboxing).
    • Sticking to the principles of "clean code" (readability, maintainability, meaningful commenting) even under time pressure.
    • Critically reflect on whether the chosen software architecture meets the requirements or whether refactoring is necessary.

    Contents

    The project week is held as a five-day block course following the lecture "Object-oriented programming and data structures" and includes the development of console applications for given tasks in individual and team work. In-depth knowledge of the contents of "Object-oriented programming and data structures" is assumed.

    Teaching methods

    Processing programming tasks on the computer in teamwork.

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a project-related programming assignment in a team with a presentation and a subsequent oral examination. The performance is not graded.
    Duration of the oral examination: 15 - 20 minutes.

    Requirements for the awarding of credit points

    • In order to enable teamwork and to be able to accompany the professional creation of the programs by the teachers, a minimum attendance requirement with active participation of 80% is required.
    • Recognizable personal contribution to the code created in the team, appropriate to the scope.
    • Passing the oral exam.

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • D. Ratz, D. Schulmeister-Zimolong, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 9. Auflage, Hanser, 2024
    • C. Ullenboom, Java ist auch eine Insel, 17. Auflage, Galileo Press, 2023
    • A. Solymosi, U. Grude, Grundkurs Algorithmen und Datenstrukturen in JAVA, Springer Vieweg 2017
    • R. Sedgewick, K. Wayne, Algorithmen: Algorithmen und Datenstrukturen, 4. Auflage, Pearson Studium 2014

    Programmierkurs Anwendungsentwicklung
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      42021

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Providing the knowledge required to implement application software from a professional point of view. This includes the realization of graphical user interfaces, the connection of technical concept classes and the persistence of data. Concepts of object-oriented programming are applied in a problem-oriented manner.

    Technical and methodological competence:

    • Implementing flexible systems through the use of polymorphism and interfaces
    • Recognizing the advantages of regulated exception handling
    • Implementing a flexible graphical user interface using components and layout managers
    • Using data streams
    • Identifying and solving concurrent programming problems
    • Reusing components via the targeted use of an application programming interface (API)


    Interdisciplinary methodological competence:

    • Application of programming techniques in the implementation of commercial, technical and multimedia applications

    Contents

    • In-depth study of object-oriented programming in Java (abstract classes, interfaces, polymorphism)
    • Professional exception handling via exceptions
    • Use of collections for object management
    • Access to the file system and organization of files (Java IO)
    • Use of data streams
    • Serialization of objects
    • Programming graphical user interfaces (JavaFX)
    • Event handling
    • Concurrent programming (threads)
    • Java Stream API and lambda expressions
    • Architecture of application programs from an implementation perspective

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Horstmann, C., Cornell, G.; "Core Java, Volume 1: Fundamentals", Pearson, Boston, 2018
    • Horstmann, C., Cornell, G.; "Core Java, Volume 2: Advanced Feature", Prentice Hall, Boston, 2016
    • Krüger, G., Hansen, H.; "Java-Programmierung - Das Handbuch zu Java 8", O'Reilly Verlag, Köln, 2014
    • Urma, R.-G., Fusco, M., Mycroft, A.; "Java 8 in Action: Lambda, streams, and functional-style programming", Manning, 2015
    • Epple, A.; "Java FX 8", dpunkt.verlag, Heidelberg, 2015
    • Sharan, K.; "Learn JavaFX8", Apress, Springer Science, New York, 2015
    • Sierra, K., Bates, B.; "Head First Java", O'Reilly, 2005

    Rechnerarchitektur und Betriebssysteme
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      43431

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding

    The students:

    • have a basic understanding of the structure and operation of a computer, from digital logic circuits to complete computer architectures.

    • understand the computer-oriented representation of information, in particular the coding of numbers and characters.

    • know the basic concepts of a microprocessor and its interaction with other components of a computer system.

    • have a theoretical understanding of the core functionalities of an operating system, including process, memory and file management.

    • understand the basic principles of concurrent programming and its challenges.

    Use, application and generation of knowledge

    Students are able to:

    • describe digital logic gates and explain how they work.

    • sketch and understand the structure and operation of microprocessors and computer systems.

    • analyze and evaluate different implementations of important operating system functionalities.

    • understand and practically apply the basic mechanisms of process management, memory management and file management of an operating system.

    • to use the Linux operating system for simple system programming tasks.

    • identify the challenges of concurrent programming and name suitable solutions.

    Communication and cooperation

    The students:

    • work in pairs on programming tasks and solve problems collaboratively.

    • present their solutions to the supervisor in an understandable and comprehensible way.

    • are able to discuss problems constructively and develop solution strategies together.

    • reflect on and evaluate proposed solutions in discussions with other students and lecturers

    Scientific self-image / professionalism

    The students:

    • acquire the ability to independently familiarize themselves with new concepts in computer architecture and operating systems.

    • reflect on the challenges and limitations of computer architectures and operating system concepts.

    • develop systematic problem-solving thinking, especially in the area of concurrent programming.

    • recognize the importance of teamwork and cooperation in software development and technical computer science.

    • have the basics to learn and apply advanced concepts in advanced modules.

     

    Contents

    • Number and character representation in the computer
    • Basics of digital logic
    • Computer architecture (layer model, machine types, computer structure, current processors, virtualization)
    • Simple machine programs
    • Operating system concepts (architectures, structures, processes, memory management, file systems)
    • Introduction to the practical application of Linux
    • Concurrency and inter-process communication

     

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination (90 minutes)
    • semester-accompanying coursework (bonus points)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Medical Informatics
    • Bachelor of Software and Systems Engineering (dual)

    Literature

    • Tanenbaum, A.S.; Computerarchitektur: Strukturen - Konzepte - Grundlagen, Pearson Studium, 2006
    • Stallings, W.; Operating Systems; Prentice Hall, Auflage 9, 2017

    Theoretische Informatik
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      42041

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    • Be able to name basic terms and properties of formal languages, grammars and the corresponding automata
    • .
    • Create grammars and automata for formal languages and understand how they work.
    • Be able to convert the representation of languages between grammars, automata and regular expressions.
    • Be able to independently assess problems as formal languages and classify them with regard to the language types in the Chomsky hierarchy.

    Interdisciplinary methodological competence:

    • Be able to independently assess and classify problems in terms of their complexity
    • .

    Contents

    • Formal languages and grammars: Alphabet; words: languages; grammars; derivations; grammar types in the Chomsky hierarchy
    • Regular languages: programming finite automata (deterministic and non-deterministic); minimization of automata; regular expressions; conversion between grammars, automata and regular expressions; closure properties, pumping lemma for regular languages
    • Context-free languages: pushdown automata; Chomsky normal form; word problem with the CYK algorithm; termination properties; pumping lemma for context-free languages
    • Turing machines: variants (deterministic and non-deterministic); universal Turing machines; Gödel number; P/NP problem

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Solving practical exercises in individual or team work
    • Group work
    • Individual work
    • Presentation
    • Mini-exams during the semester for regular feedback

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination
    • study achievements during the semester (bonus points)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Computer Science Dual

    Literature

    • Hopcroft, J.E., Motwani, R., Ullman, J.D.; Einführung in die Automatentheorie, Formale Sprachen und Berechenbarkeit; Pearson Studium; 3. Auflage; 2011
    • Hoffmann, D.W.; Theoretische Informatik; Hanser; 5. Auflage; 2022
    • Hedtstück, U.: Einführung in die Theoretische Informatik; Oldenbourg; 5. Auflage; 2012
    • Erk, K., Priese, L.; Theoretische Informatik; Springer; 4. Auflage; 2018

    3. Semester of study

    Informationssysteme im Gesundheitswesen
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      44441

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Subject and methodological competence:
    After completing the module, students will be able to name the most important information systems in the healthcare sector, how they work and their special features. Furthermore, students will be able to evaluate the various information systems with regard to their area of application and point out the advantages and disadvantages of the various solutions. In addition, students are able to independently develop solution and system concepts for given practical application scenarios.
    Among other things, students are able to

    • describe the structure of an electronic patient record and explain the differences and areas of application of ePA, eFA, eGA
    • the students know the basics of medical information systems and can apply them to specific examples
    • name the modules of hospital information systems and practice management systems and assign the essential supported processes
    • to parameterize
    • an information system
    • name the structure and areas of application of HL7, DICOM and IHE
    • name the structure of the telematics infrastructure (TI) and TI applications, explain how they work and differentiate between the individual solutions
    • to reproduce the essential legal framework
    • to transfer knowledge about the functionality of available eHealth applications to specific use cases in order to develop solutions for supporting medical processes in the healthcare sector
    Social competence:
    • They know the essential soft factors when using IT in healthcare
    Professional field orientation:
    • They are familiar with the major providers of hospital information systems and their use
    • they know what types of information systems are available on the market
    • they know the common communication standards and terminology in the professional field of medical informatics
    • they know the basic solution approaches for essential support requirements in the healthcare sector and can transfer these to comparable scenarios

    Contents

    • Basics of medical information systems
    • Structure and concepts of electronic patient records and other record systems
    • Modules and supported core processes of a hospital information system
    • Functions and supported core processes of a medical practice system
    • Basic communication standards in healthcare such as HL7 FHIR, DICOM, IHE, openEHR (syntactic interoperability)
    • Fundamentals of basic terminologies such as ICD, OPS, SNOMED-CT (semantic interoperability)
    • Legal framework (KHZG, E-Health Act, DVG, ...)
    • Development of the telematics infrastructure and applications on it (DiGAs, teleconsultations, KIM and others)
    • Example applications of eHealth: eGK, ePrescription, eMedication, health portal, telemedicine, eDocumentation
    • Parameterization of a hospital information system

    Teaching methods

    • Seminar-style lecture, with blackboard writing and projection
    • Processing of exercises during the lecture, possibly on the computer in individual or team work
    • Active, self-directed learning through the use of electronic learning materials
    • Excursion

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam, 60 - 90 minutes

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Baas, J. (2020). Digitale Gesundheit in Europa: menschlich, vernetzt, nachhaltig. Medizinisch Wissenschaftliche Verlagsgesellschaft.
    • Bachmann, W. (2009). Praxishandbuch IT im Gesundheitswesen: Erfolgreich einführen, entwickeln, anwenden und betreiben. Hanser Verlag.
    • Dugas, M. (2017). Medizininformatik. Springer Berlin Heidelberg.
    • Haas, P.: Medizinische Informationssysteme und Elektronische Krankenakten, Springer 2004.
    • Jehle, R., Czeschik, J. C., Freund, T., & Wellnhofer, E. (Eds.). (2015). Medizinische informatik kompakt: Ein Kompendium für mediziner, informatiker, qualitätsmanager und epidemiologen. Walter de Gruyter GmbH & Co KG.
    • Johner, C., Hölzer-Klüpfel, M., & Wittorf, S. (2020). Basiswissen medizinische Software: Aus-und Weiterbildung zum certified professional for medical software. dpunkt. verlag.
    • Leiner, F. (2012). Medizinische Dokumentation: Grundlagen einer qualitätsgesicherten integrierten Krankenversorgung; Lehrbuch und Leitfaden; mit 24 Tabellen. Schattauer Verlag.
    • Marx, G. (2021). Telemedizin: Grundlagen und praktische Anwendung in stationären und ambulanten Einrichtungen. Springer.
    • Simon, M. (2021). Das Gesundheitssystem in Deutschland: Eine Einführung in Struktur und Funktionsweise. Hogrefe AG.
    • Krankenhausinformationssystem M-KIS der Meierhofer AG (steht im Labor zur Verfügung) mit entsprechenden Handbüchern

    Diagnose- und Therapiesysteme für die Medizin
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      43451

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    After completing the module, students will be able to

    • explain and outline the basic physical and mathematical processes of medical signaling and imaging
    • describe and classify the technical operating principles of common medical devices
    • name the most important diagnostic and therapeutic systems, demonstrate their possibilities and limitations and differentiate and independently evaluate their interaction
    • recognize and classify biosignals and medical images
    • describe and classify clinical workflows
    • describe and classify the change in radiology and medical technology from digitalization to artificial intelligence

    Social skills:

    • Working on and solving tasks in smaller teams, such as the mutual derivation of biosignals or targeted experimentation with an ultrasound device

    Professional field orientation:

    • Knowing and classifying internationally standardized diagnostic and therapeutic systems typical of the profession and their clinical processes
    • Processing and solving mathematical-technical problems with the standard software Matlab®, which is widely used in industry

    Contents

    • Introduction and motivation: outline of the historical development of medicine and medical technology
    • Introduction to the most important medical diagnostic and therapeutic systems, their interaction and differentiation, as well as their clinical workflows: endoscopy, sonography, radiography, fluoroscopy, computer tomography, magnetic resonance tomography, nuclear imaging, interventional radiology, radiotherapy, image-guided surgery
    • Basics of digital signal processing (practical course): Introduction to the Matlab® system for solving mathematical-technical problems
    • Physics, technology and applications of the most important biosignals: electrocardiography (ECG), electroencephalography (EEG), electromyography (EMG) and electrooculography (EOG)
    • Physics, technology and applications of the most important imaging techniques: Microscopy/endoscopy, X-ray imaging, computed tomography, ultrasound, magnetic resonance tomography
    • Mathematical methods of medical 3D imaging: image reconstruction
    • Introduction to methods of machine learning and artificial intelligence (MLP, neural convolutional networks) and their applications in radiology and medical technology

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Dössel, O.; Bildgebende Verfahren in der Medizin; Springer; 2. Auflage; 2016
    • Prokop, M.; Spiral and Multislice Computed Tomography of the Body; Thieme; 2. Auflage; 2013
    • Bushberg, J.; The Essential Physics of Medical Imaging ; Lippincott Williams & Wilkins; 3. Auflage; 2011
    • Handels, H.; Medizinische Bildverarbeitung; 1. Auflage; 2009
    • Epstein, C.; Introduction to the Mathematics of Medical Imaging; Prentice Hall; 1. Auflage; 2003.
    • Morneburg, H.; Bildgebende Systeme für die medizinische Diagnostik; 3. Auflage; Siemens, 1995

    Online textbook:

    • Sprawls, P.; The Physical Principles of Medical Imaging, 2nd Ed.: http://www.sprawls.org/ppmi2/

    Softwaretechnik 1
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      43051

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60h

    • Self-study

      90h


    Learning outcomes/competences

    After successfully completing the module, students will be able to
    
    - understand relevant procedure and process models of software development,
    - apply suitable methods, languages, techniques and tools of requirements engineering,
    - analyze contradictions, incompleteness and inconsistencies in requirements documents,
    - apply methods, languages and tools for GUI prototyping,
    - understand the methodical approach to object-oriented analysis,
    - create the following UML diagrams:
    UML use case diagram
    UML class diagram
    UML activity diagram
    UML sequence diagram
    UML communication diagram
    UML state diagram
    - work cooperatively and collaboratively in student project teams,
    - create a requirements specification,
    - specify a UML-based OOA model for a software system,
    - create a suitable static GUI prototype,
    - present their own results in a lecture,
    - describe and summarize their own results in a written project paper
    .

    Contents

    • Methods, processes, activities, roles and responsibilities in requirements engineering
      Process models in software development
      Methods and modeling languages for object-oriented analysis
      Object-oriented analysis with UML: Static and dynamic aspects
      UML use case diagram
      UML package diagram
      UML activity diagram
      UML object diagram
      UML sequence diagram
      UML state diagrams
      Checklists for the OOA model
      Components and contents of the OOA documentation

     

    Teaching methods

    • Lecture in dialog with the students, with blackboard inscription and slide projection
      Practical course accompanying the lecture
      Processing of UML modeling tasks on the computer in individual and/or team work
      Presentations of the results obtained by the students

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The examination for the Software Engineering 1 teaching module consists of three partial examinations.
    
    At the beginning of the semester, the students form project groups of four people each, who can each choose a software topic (from several given ones). Over the course of the semester, a student project group then develops the following results as part of the object-oriented analysis of their software topic and makes these twelve results continuously available on a web portal:
  • Project vision
    2. personas and scenarios
    3. UML use case diagram
    4. templates for finished use case specifications
    5. requirements specification
    6. GUI prototype
    7. CRC cards
    8. UML class diagram
    9. UML activity diagrams
    10. UML sequence diagrams
    11. UML state diagrams
    12. project work in which the results obtained are summarized and described
    
    1st partial examination: Results 1 to 6 are presented by two students in a 20-minute presentation in the middle of the lecture period. A maximum of 30 points can be achieved for results 1 to 6, including the presentation.
    2nd partial examination: Results 7 to 11 are presented by two further students in a 20-minute lecture at the end of the lecture period. A maximum of 35 points including presentation can be achieved for the results of grades 7 to 11.
    3rd partial examination: After the lecture period, four weeks are available to complete the project work (result 12). The project work is then handed in and assessed. A maximum of 35 points can be achieved for the written project work.
    
    The overall grade is calculated from the sum of the three partial results:
    
    From 50 points, a grade of 4.0 (sufficient) is awarded.
    From 95 points, the grade 1.0 (very good) is awarded
    .
  • Requirements for the awarding of credit points

    From 50 points, a grade of 4.0 (sufficient) is awarded. From 95 points, a grade of 1.0 (very good) is awarded

    .

    Applicability of the module (in other degree programs)

    • Bachelor of Medical Informatics
    • Bachelor of Computer Science
    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)

    Literature

    • Balzert, H. (2005): Lehrbuch der Objektmodellierung (2. Aufl.), Heidelberg: Spektrum Akademischer Verlag.
    • Balzert, H. (2009): Lehrbuch der Softwaretechnik - Basiskonzepte und Requirements Engineering (3. Aufl.), Heidelberg: Spektrum Akademischer Verlag.
    • Ludewig, J.; Lichter, H. (2023): Software Engineering - Grundlagen, Menschen, Prozesse, Techniken, 4. korrigierte und überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
    • Oestereich, B., Scheithauer, A. (2013): Analyse und Design mit UML 2.5, 11. Auflage, München: Oldenbourg Verlag.
    • OMG (2017): UML Specification Version 2.5.1, http://www.omg.org/spec/UML/2.5.1/PDF.
    • Pichler, R. (2008): Scrum, Heidelberg: dpunkt-Verlag.
    • Pohl, K., Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
    • Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.
    • Vollmer, G. (2024): Unterlagen zur Lehrveranstaltung "Softwaretechnik 1".
    • Sommerville, I. (2018): Software Engineering, 10. Auflage, München: Pearson Studium.

    Telematik und Telemedizin
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      45442

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding

    The students:

    • know the motivation and benefits of telematics and telemedicine applications in medicine

    • understand the care processes in the healthcare system and the role of telematics applications in improving patient care.

    • are familiar with the different classes of telematics applications and can differentiate between their areas of application.

    • are familiar with the legal framework (in particular SGB regulations) and data protection aspects in the context of eHealth solutions.

    • understand problems and solution approaches in distributed open systems and integration techniques with a special focus on web services.

    • know special interoperability aspects in healthcare and relevant standards such as IHE/XDS, FHIR and CDA.

    • are familiar with the architecture and applications of the national healthcare telematics platform.

    • understand the concepts and challenges of cross-facility electronic health record systems (eEPA)

    • are familiar with central eHealth applications such as eMedication plan, emergency data set, electronic patient file (ePA), KIM, MIOs and patient short file.

    • are familiar with pHealth and mHealth solutions and understand their importance for patients and the role of digital health applications (DiGAs)

    • know the importance of patient portals for inpatient care and the involvement of patients in the care process.

    • understand the basic application types of telemedicine solutions and their potential to support medical care.

    • know relevant international standards such as FHIR, IHE/XDS, CDA and SNOMED and their importance for interoperability in healthcare.

    Use, application and generation of knowledge

    Students are able to:

    • analyze and evaluate various integration approaches for networking medical information systems.

    • to use web services as a central technology for the interoperability of telematics and telemedicine applications.

    • Design telematics and telemedicine applications with the integration of patient apps and assess their added value for patient care.

    • to use relevant international standards such as FHIR, IHE/XDS and SNOMED for specific use cases in the healthcare sector.

    • to develop innovative solutions to improve the interoperability of medical information systems and to expand existing systems.

    Communication and cooperation

    The students:

    • are able to discuss challenges and solutions in the field of eHealth in a technically sound manner.

    • present their analyses and solution concepts in a structured and understandable way for specialist audiences and interdisciplinary teams.

    • work in teams on the design and development of telematics and telemedicine applications and reflect critically on the results of their work.

    • can clearly communicate regulatory and technical requirements in discussions and identify suitable solutions.

    • develop problem-solving strategies in an interdisciplinary exchange with experts from medicine, IT and health economics.

    Scientific self-image / professionalism

    The students:

    • reflect on the social and ethical implications of eHealth technologies and telematics applications.

    • have the ability to independently familiarize themselves with new technological developments and regulatory frameworks.

    • apply scientific methods to analyze and evaluate interoperability solutions in the healthcare sector.

    • develop a well-founded awareness of challenges in digital healthcare and can formulate well-founded approaches to solutions.

    • understand themselves as part of an interdisciplinary specialist community and are able to contribute their knowledge to research and practice.

    Contents

    After a brief introduction to motivation, the current situation in Germany and current legislation on telematics/telemedicine, the course is divided into four main parts with the following content:

    • Distributed open systems - problems and solution approaches The national
      • What are distributed open systems
      • Integration levels, approaches and technologies
      • Necessary central platform artefacts such as terminology and reference services
      • the role of semantic reference systems for semantic interoperability, in particular SNOMED
    • Telematics applications according to application classes
    • National telematics platform and its applications
    • Applications by application class
      • Applications for communication (e.g. eArztbrief, eMeldung, KIM, eMessanger)
      • Applications for documentation (e.g. eEmergency data, electronic patient file, patient short file)
      • Applications for collaboration (DIGAs, case management, second opinion center, patient-physician collaboration, etc.)
      • Applications for knowledge support (AMTS, guideline deployment, application of clinical pathways, etc.)
    • Telemedicine applications
      • Applications for medical collaboration (teleradiology, telepathology, televisit etc.)
      • Applications for tele-monitoring
      • mHealth and pHealth applications for patients
      • Other applications

    In each case, practically realized examples are discussed and partly demonstrated.

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Project work accompanying the lecture with final presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Semester-accompanying examinations (presentations, papers) amounting to 40% of the overall grade
    • Final project work with presentation (30 minutes) amounting to 60% of the overall grade 

    Requirements for the awarding of credit points

    Semester-accompanying examination and final project work are assessed with at least a pass

    .

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Albrecht U-V (Hrsg.) (2016) Chancen und Risiken von Gesundheits-Apps CHARISMHA. Medizinische Hochschule Hannover. URL: http://www.charismha.de/ (abgerufen am 18. November 2018)
    • Coulouris G., Dollimore J., Kindberg T.: Verteilte Systeme. Konzepte und Design. Pearson Studium München 2002.
    • Fischer F, Krämer A.: eHealth in Deutschland - Anforderungen und Potenziale innovativer Versorgungsstrukturen. Springer Berlin Heidelberg 2016.
    • Haas P.: Gesundheitstelematik. Grundlagen Anwendungen Potenziale. Springer Heidelberg 2006.
    • Haas P., Meier A., Sauerburger H.: E-Health. Praxis der Wirtschaftsinformatik. HMD 251. dpunkt.Verlag Heidelberg 2006.
    • Haas P (2017) Elektronische Patientenakten Einrichtungsübergreifende Elektronische Patientenakten als Basis für integrierte patientenzentrierte Behandlungsmanagement-Plattformen. Bertelsmann Stiftung. Gütersloh.
    • Knöppler, K.; Neisecke, T.; Nölke, L. (2016) Digital Health-Anwendungen für Bürger. Kontext, Typologie und Relevanz aus Public-Health-Perspektive Entwicklung und Erprobung. Bertelsmann Stiftung. Gütersloh.
    • Marx. G., Rossaint R., Marx N. (Hrsg.) (2021) Telemedizin. Grundlagen und praktische Anwendung in stationären und ambulanten Einrichtungen. Springer Verlag 2021
    • Melzer I.: Service-orientierte Architekturen mit Web Services. Springer Heidelberg 2010.
    • Müller G., Eymann T., Kreutzer M.: Telematik- und Kommunikationssysteme in der vernetzten Wirtschaft. Oldenbourg München 2003.
    • Diverse HL-7 und IHE-Standards-Papiere

    Web-Technologien
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      46898

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding: After completing this module, students will be able to

    • name the central basic principles and concepts of the WWW (e.g. client-server, HTTP) and the Internet (e.g. protocols) and classify them in the context of web applications,
    • distinguish between client-side and server-side web development techniques,
    • understand and explain the syntax, semantics and concepts of the central technologies of the web platform (HTML, CSS and JavaScript), and
    • recognize basic, technology-independent architectural aspects of web applications (e.g. model-view-controller, event-driven and asynchronous programming) and transfer them to specific technologies.


    Use, application and generation of knowledge: After completing this module, students will be able to

    • specify the structure of a web interface using HTML in a semantically correct and accessible way,
    • implement the layout of a web application responsively using CSS,implement client- and server-side logic using JavaScript,
    • to use essential web development tools, such as development environments and build management tools,
    • and thus realize small to medium-sized web applications for specific tasks.


    Communication and cooperation: After completing this module, students will be able to

    • develop and implement solutions cooperatively in a team, and
    • explain and discuss their ideas and solutions, e.g. in the form of short presentations or code reviews
    • .


    Scientific self-conception/professionalism: After completing this module, students will be able to

    • apply industry best practices in the field of web development, and
    • justify their technical solutions for typical tasks in web development
    • .

    Contents

    Module description: 
    In this module, students gain an overview of the central technologies of the web platform, which forms the basis of modern web applications. After completing the module, they will have mastered the central principles and concepts of these technologies and will be able to use them to implement small to medium-sized web applications for specific tasks.

    Module structure:
    The module covers the following topics:

    1. Overview of the central concepts and technologies of the WWW and the Internet (e.g. client-server architecture, protocols and standards such as TCP, IP, DNS, URL, HTTP)
    2. Client-side concepts and technologies for the development of web applications:
      1. HTML (incl. semantics, accessibility)
      2. CSS and responsive web design
      3. JavaScript and browser APIs (e.g. DOM, AJAX)
    3. Server-side concepts and technologies for the development of web applications:
      1. Basic concepts: event-driven and asynchronous programming, request handling, modularization (e.g. with Node.js)
      2. Structuring using model view controllers 

    Teaching methods

    • Flipped/Inverted Classroom:
      • Online e-learning materials with interactive slides and videos (asynchronous self-study)
      • Interactive face-to-face events for tasks and exercises based on practical examples, for additional in-depth study and for answering and discussing questions; just-in-time teaching based on accompanying questions
    • Project-oriented internship: project task that is worked on in teams throughout the semester
    • Guest lectures with experts and current topics from the industry

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Written examination (scope: 100%, duration: 120 minutes); semester-related coursework (bonus points, scope: 13%)

    Requirements for the awarding of credit points

    Passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual

    Literature

    • Wolf, Jürgen (2023): HTML und CSS: Das umfassende Handbuch, 5. Auflage, Rheinwerk Computing
    • Bühler, Peter; Schlaich, Patrick; Sinner, Dominik (2023): HTML und CSS: Semantik - Design- Responsive Layouts, 2. Auflage, Springer Vieweg
    • Simpson, Kyle (2015-2020): You Don’t Know JS (Yet), Band 1-6, O’Reilly/Independently published
    • Haverbeke, Marijn (2020): JavaScript: Richtig gut programmieren lernen, 2. Auflage, dpunkt.verlag
    • Springer, Sebastian (2021): Node.js: Das umfassende Handbuch, 4. Auflage, Rheinwerk Computing
    • Tilkov, Stefan; Eigenbrodt, Martin; Schreier, Silvia; Wolf, Oliver (2015): REST und HTTP: Entwicklung und Integration nach dem Architekturstil des Web, 3. Auflage, dpunkt.verlag
    • Tanenbaum, Andrew S.; Feamster, Nick; Wetherall, David J. (2024): Computernetzwerke, 6. Auflage, Pearson Studium

    Relevante Standards:
    • WHATWG (2025): HTML Living Standard, https://html.spec.whatwg.org/
    • W3C (2025): CSS Specifications, https://www.w3.org/Style/CSS/specs.html
    • Ecma International (2025): ECMA-262: ECMAScript® 2025 language specification, 16th Edition, https://tc39.es/ecma262/
    • WHATWG (2025): DOM Living Standard, https://dom.spec.whatwg.org

    4. Semester of study

    Mathematik für Informatik 4 (MI)
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      43075

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After attending the course, students will have acquired the following skills.

    Professional and methodological competence (knowledge and skills):

    - know the terminology of medical statistics, epidemiology and biometrics and can use these confidently in the professional field of medical informatics.
    - can use methods of descriptive statistics to describe data and associations manually and with computer support in the statistical programming language R.
    - can select and perform statistical tests for specific problems and interpret the results.
    - know the regulatory and ethical requirements for clinical studies
    - can use the specific statistical methods of medicine (e.g. survival time analyses, logistic regression).
    - can visualize statistical data and provide simple interpretations
    - can critically scrutinize study results
    .

    Interdisciplinary methodological competence:
    - can critically question statistical results of general studies and also analyze simple studies in non-medical contexts.

    Competencies (personal and social skills)
    - can formulate ideas and proposed solutions orally and in writing
    - can solve tasks in exercises and practicals independently and present the results
    - can develop solutions cooperatively in the exercise and practical phases
    - can argue in discussions in a goal-oriented manner and deal with criticism objectively
    - can recognize and resolve misunderstandings between discussion partners

    Contents

    - Descriptive statistics and linear regression manually and with the statistical programming language R
    - Epidemiological measures
    - Repetition of statistical terminology in the context of medicine (distributions, random variables, confidence intervals) - inverted classroom
    - Medical statistical decision support
    - Analysis of diagnostic tests
    - Analysis of survival times
    - Clinical studies and drug trials
    - Inferential statistics in medicine
    - Logistic regression with applications from medicine
    - Medical statistical tests with application examples from medicine
    - Study types, design and evaluation methods
    - Literature research of medical studies
    - Molecular genetic principles and genetic association studies

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Processing programming tasks on the computer in individual or team work
    • inverted classroom

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination
    • study achievements during the semester (bonus points)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    - C. Weiß, Basiswissen Medizinische Statistik, 8. Auflage, Springer (2025)
    - G. Teschl und S. Teschl, Mathematik für Informatiker 2, 4. Auflage, Springer (2013) - im Intranet der FH elektronisch verfügbar
    - J. Groß, Grundlegende Statistik mit R, Vieweg, (2010) - im Intranet der FH elektronisch verfügbar
    - M. Oestreich und O. Romberg, Keine Panik vor Statistik, 7. Auflage, Vieweg (2023)
    - R.-D. Hilgers, P. Bauer und V. Scheiber, Einführung in die Medizinische Statistik, Springer (2006)

    Kommunikations- und Rechnernetze
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      46832

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    After completing the course, students will be able to

    • Understand the principles, protocols and architecture of the internet
    • Use elementary commands of the Linux and Windows operating systems for network configuration and network testing
    • Perform and interpret protocol and network analyses with analysis tools
    • Analyze existing wired and wireless networks
    • Design and implement wired and wireless networks
    • Configure network components (router, switch) including VLAN and NAT

    Contents

    • Reference models (ISO/OSI, TCP/IP)
    • Bit transmission layer, transmission media
    • Ethernet, network components: Hub, switch, router; virtual LANs (VLAN)
    • IP protocols, addressing, routing
    • Network Address Translation (NAT)
    • Protocols of the transport layer
    • IPv6, IPSec, SSL/TLS
    • Wireless communication

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination
    • study achievements during the semester (bonus points)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science Dual

    Literature

    • Andrew S. Tanenbaum, David J. Wetherall; Computernetzwerke; Pearson Studium; 5. Auflage; 2012
    • Douglas E. Comer, Ralph Droms; Computernetzwerke und Internets; Pearson Studium; 3. Auflage; 2001

    Künstliche Intelligenz
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      46834

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Fundamental knowledge of concepts and methods of artificial intelligence (AI) and of applications of knowledge-based methods in "intelligent systems". Basic understanding of the possible applications of these methods. Sensitivity for practice-relevant questions.

    Technical and methodological competence:

    • Capturing and presenting typical AI software architectures
    • .
    • Understanding and explaining the paradigms of symbolic and sub-symbolic approaches to AI.
    • In-depth explanation and demonstration of heuristic methods of symbolic AI: search, constraints, rule processing. Basic understanding of uncertainty and fuzziness in the context of knowledge-based applications.
    • Develop the ability to apply these methods in the context of simple problems.
    • Design and implement small agent programs.
    • Understanding and applicability of basic formal logic modeling techniques in the field of AI.

    Social skills:

    • Development of verbal skills and communication skills in a team by working out solutions in small groups
    • .

    Contents

    • Basic concepts of artificial intelligence and formal knowledge processing
    • Intelligent agents
    • State spaces and heuristic search, alpha-beta search, constraint propagation
    • Production control systems
    • Uncertain knowledge (probabilism), vague knowledge (fuzzy methods)
    • Simple neural networks
    • Formal logic modeling in the field of artificial intelligence (e.g. predicate logic)

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • immediate feedback and success monitoring

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Written examination paper [scope: 100%] (90 minutes)
    • Semester-accompanying coursework (bonus points): Programming tasks [scope: 15%], credit only for a passed written exam paper

    Requirements for the awarding of credit points

    Passed written examination

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Business Informatics
    • Bachelor of Computer Science Dual

    Literature

    • Ingo Boersch, Jochen Heinsohn, Rolf Socher; Wissensverarbeitung. Eine Einführung in die Künstliche Intelligenz für Informatiker und Ingenieure ; 2. Auflage; Spektrum Akademischer Verlag; München; 2007.
    • Stuart Russel, Peter Norvig: Künstliche Intelligenz. Ein moderner Ansatz ; 3. aktualisierte Auflage; Pearson; München; 2012.

    Softwaretechnik 2
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      44121

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Introduction to software architecture. Technological implementation of technical requirements from the requirements specification and functional requirements from the OOA model.

    Technical and methodological competence:

    • Differentiation between analysis, rough draft (architecture) and detailed draft (design)
    • Naming different architectural styles and metaphors
    • Naming and applying architectural patterns
    • Name and apply different middleware approaches for presentation, communication, persistence, application logic and control
    • Describe and carry out a criteria-based evaluation
    • Specification of an architecture model (component diagram, distribution diagram)
    • Documentation of the design based on relevant UML description tools (e.g. packages, activity diagram, class diagram, state diagram, scenario)
    • Name and apply design patterns according to Gamma
    • Name, describe and differentiate between solution approaches for cross-cutting tasks such as logging, security, persistence, transaction protection
    • Classify different concepts in the architecture toolbox

    Interdisciplinary methodological competence:

    • Precise description of software systems from a wide range of application domains
    • Recognizing contradictions, incompleteness, inconsistencies
    • Modeling architectures using the UML
    • Integrating specific lectures and their content, such as web engineering or databases, into the architecture toolbox

    Social skills:

    • Systematically analyze problems of medium complexity in a team
    • Develop a software architecture in a cooperative and collaborative team
    • Implement a software architecture with the help of middleware in a cooperative and collaborative team

    Contents

    • The role of the software architect
    • Architectural design (introduction and overview)
    • Architectural design (approach and documentation)
    • Architectural styles and metaphors
    • Architectural patterns
    • Object-oriented design
    • Design patterns
    • Enterprise concepts (or cross-cutting tasks: security, persistence, transactions, )
    • Basic architectures
    • Technology selection
    • OOD documentation

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Group work
    • Seminar

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination
    • study achievements during the semester (bonus points)

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Medical Informatics
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor of Business Informatics

    Literature

    • Balzert, H.: Lehrbuch der Objektmodellierung, 2. Auflage, Spektrum-Verlag, 2005
    • Ludewig, J.; Lichter, H.: Software Engineering: Grundlagen, Menschen, Prozesse, Techniken
    • Reussner, R.; Hasselbring, W.: Handbuch der Software-Architektur, Vol. 2. Aufl. dpunkt Verlag, Heidelberg, 2008.
    • Rupp, C.; Queins, S.: UML 2 glasklar, Praxiswissen für die UML-Modellierung, 8. Auflage, Hanser-Verlag 2017.
    • Starke, G.: Effektive Software-Architekturen: Hanser-Verlag, 2009, 4. Auflage
    • Starke, G.; Hruschka, P. arc42 in Aktion: Hanser-Verlag 2016

    Visualisierung und Interaktion für die Medizin
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      47719

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding:

    After successfully completing the module, students will be able to:

    • List and explain the diverse areas of application of the visualization of and interaction with medical data in modern healthcare
    • describe examples of human-machine interaction in medical technology and weigh up their advantages and disadvantages
    • describe and analyze the interaction of the various sub-areas of graphical data processing in the development of current medical diagnostic and therapeutic systems
    • explain important concepts of geometric modeling and computer graphics such as projection, camera, lighting and texturing and classify their practical use
    • explain the WebGL programming interface for interactive 2D and 3D graphics in the web browser and outline the interaction of JavaScript API, rendering pipeline, shader programming and hardware acceleration on the GPU graphics card
    • .


    Use, application and generation of knowledge:

    After successfully completing the module, students will be able to:

    • use WebGL to visualize and test simple 2D and 3D graphic models in the web browser by developing a simple single-file application containing HTML, CSS, JavaScript and WebGL code
    • extend their created visualizations with interactive elements such as GUI components and mouse interactions
    • extend, test and further develop a given object-oriented multi-file WebGL framework step by step with models, transformations, cameras, lighting and texturing


    Communication and cooperation:
    After successfully completing the module, students will be able to:

    • work on and solve programming tasks in small teams on the computer
    • experiment in small groups in a targeted manner, for example to gradually increase the complexity of interaction possibilities


    Scientific self-image / professionalism:
    After successfully completing the module, students will be able to:

    • to assess the importance of thinking and acting in a quality-oriented and responsible manner
    • to recognize the need for lifelong learning in order to keep pace with advances in medicine and technology
    • solve technical issues typical to the profession, such as the visualization of medical data in a web browser, using industry standards such as HTML, CSS, JavaScript and WebGL code
    • justify and justify the use of their chosen technologies to professional representatives

    Contents

    • Introduction and motivation: Importance of the subfields of computer graphics (geometric modeling and image synthesis), image processing and 3D computer vision (object reconstruction from projections) in the development of current medical diagnostic and therapeutic systems
    • Overview of current standard software for the visualization of medical image data
    • Introduction to the programming interface (lecture and practical course) OpenGL / WebGL. Expansion of Matlab® knowledge
    • The human eye, color perception, color models and transformation
    • Basic elements and algorithms of geometric modeling for generating surface models from medical image data: Points, interpolation, polygon meshes, curves, surfaces, marching cubes
    • Basics and algorithms of image synthesis for the visualization and manipulation of surface models: Transformations, projection, visibility calculation and occlusion, local lighting and shading, textures, global illumination, stereo visualization
    • Basics and algorithms for direct volume visualization: orthogonal sectional images, multiplanar reformatting, curved planar reformatting, volume rendering (classification, interpolation, lighting, compositing), virtual endoscopy
    • Virtual reality and human-machine interaction in medical technology: input and output devices, tracking systems, stereo displays, haptic visualization using force feedback

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture and closely interlinked in terms of content in interaction with the students, with blackboard writing and projection. Explanation of the task and joint development and outlining of a solution
    • Internship accompanying the lecture and closely interlinked in terms of content; processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a written exam in which students should recall and recall basic knowledge of the visualization of medical data with the help of computer graphics, as well as the implementation of interactive user interfaces. In addition, they should be able to transfer this knowledge to practical problems and apply it where necessary. This includes creating short WebGL programs or modifying or supplementing given programs.
    Duration: 90 minutes

    Requirements for the awarding of credit points

    The written examination is graded and must be completed with a minimum grade of sufficient (4.0)

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Marschner, S., Shirley, P.; Fundamentals of Computer Graphics; CRC-Press; 5. Auflage; 2021
    • Preim, B., Botha, C.; Visual Computing for Medicine: Theory, Algorithms, and Applications (Morgan Kaufmann Series in Computer Graphics), 2. Auflage; 2013
    • Nischwitz, A. et al.; Computergrafik und Bildverarbeitung: Band I: Computergrafik; Vieweg+Teubner; 4. Auflage, 2020
    • Preim B., Dachselt R., Interaktive Systeme, Band 1 und 2: Grundlagen, Graphical User Interfaces, Informationsvisualisierung, Springer 2010
    • Engel, K. et al.;  Real-time volume graphics. A K Peters 2006

    5. Semester of study

    Informatik und Gesellschaft
    • PF
    • 2 SWS
    • 2.5 ECTS

    • Number

      45201

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    After successfully completing module I&G, students have acquired professional competence because they ...

    • can describe the subject of computer science and its significance for society
    • distinguish and explain the concepts of ethics, morality, responsibility, value and dilemma. 
    • be able to explain the main features of professional ethics in IT.
    • understand that technology design and appropriation are social processes and be able to relate this understanding to their own projects and current social IT issues.Name theories and concepts of the socio-technical perspective and be able to describe their contribution to the success of IT projects.be able to name and describe relevant representatives of IT and players in the IT environment in our society.Name and critically discuss facts about current, socially significant IT topics.

      After successfully completing the I&G module, students will have acquired self-competence because they ...

      • are able to address their responsibility as computer scientists
      • .
      • they begin to deal with their own role as computer scientists
      • .

      After successfully completing module I&G, students have acquired social competence because they ...

      • can recognize, describe and discuss the impact of IT on an individual and social level
      • .

      After successfully completing module I&G, students have acquired professional field competence because they ...

      • can derive activities from their knowledge that they can place in project procedure models

    Contents

    1. Classification of the subject computer science & society
    2. Socio-technical perspective, the importance of communication and its representation in technical systems
    3. Concepts of the sociology of technology and work and organizational psychology
    4. Ethics in computer science
    5. Socio-technical design principles and process model for IT projects
    6. Legal framework 
    7. Application of the ethical guidelines of the GI to current social issues related to IT

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Group work
    • Seminar

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • project-related work with documentation and presentation followed by an oral examination
    • oral examinations
    • Homework
    • presentations 

    Requirements for the awarding of credit points

    Module I&G is successfully completed without grading if a student ... 

    • has actively participated in at least one discussion round on the application of the ethical guidelines of the GI and was able to answer questions from the lecturer on the content. 
    • also created and presented a poster on a given topic in group work and discussed it with the auditorium 
    • .
    • also actively participated in at least one full day of the seminar and was able to answer questions from the lecturer on the content. 

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Gesellschaft für Informatik e.V. (2021): Ethischer Kompass für Informatik-Fachleute - Basierend auf den ethischen Leitlinien der Gesellschaft für Informatik. Gesellschaft für Informatik e.V. Online verfügbar unter https://gi.de/fileadmin/GI/Allgemein/PDF/GI_Ethischer_Kompass.pdf (abgerufen am 10. März 2025). 
    • Kienle, Andrea; Kunau, Gabriele (2014): Informatik und Gesellschaft - eine sozio-technische Perspektive. München: Oldenbourg. 
    • Loll, Anna Catherin (2017): Akteure im Bereich Informatik und Gesellschaft. In: Informatik Spektrum, 40, 4, S. 345-350. 
    • Pretschner, Alexander; Zuber, Niina; Gogoll, Jan; Kacianka, Severin; Nida-Rümelin, Julian (2021): Ethik in der agilen Software-Entwicklung. In: Informatik Spektrum, 2021, 44, S. 348-354. 
    • Webseite Gesellschft für Informatik
    • Webseite Netzpolitik.org
    • Webseite Humanetech
    • Webseite irights 

    Medizinisches Softwareprojekt
    • PF
    • 0 SWS
    • 7.5 ECTS

    • Number

      45195

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      2 h

    • Self-study

      223 h


    Learning outcomes/competences

    Knowledge and understanding:

    After successfully completing the module, students will be able to:

    • reproduce the phases and disciplines of software development and the associated theoretical, conceptual and practical knowledge and skills and explain their practical use
    • name the processes and methods of project management and project documentation and apply them specifically to a concrete task


    Use, application and generation of knowledge:

    After successfully completing the module, students will be able to:

    • to delve deeper into a given field of application in medical informatics
    • organize and apply their knowledge of programming languages, frameworks and tools to select suitable technologies for a specific project
    • use best practices and design patterns to create efficient and scalable software solutions
    • recognize and avoid common pitfalls and thus accelerate the development process


    Communication and cooperation:
    After successfully completing the module, students will be able to:

    • carry out a software project in a team of 10-12 developers
    • Use communication platforms and tools to keep information and updates accessible and up-to-date for all team members
    • Use collaborative tools such as versioning systems, collaborative development environments and project management tools to work in parallel and effectively towards common goals
    • Recognize conflicts early on and address them constructively before they hinder project progress


    Scientific self-image / professionalism:
    After successfully completing the module, students will be able to:

    • take an evidence- and research-based approach to creating solutions
    • Recognize the need for lifelong learning to keep pace with advances in medicine and technology
    • To think and act in a quality-oriented and responsible manner
    • to assess the importance of interdisciplinary collaboration with professionals from medicine, computer science and other disciplines

     

    Contents

    In this module, students work on the practical implementation of a software project in the field of medical informatics. At the beginning, they assess their own skills and inclinations in order to organize themselves into subgroups for tasks such as project management, documentation, development and testing.

    Depending on the number of students and the scope of the project, requirements specifications and database models can either be created by the students themselves or provided by the lecturer. A subgroup takes responsibility for project management, which includes organizing and recording project meetings as well as scheduling and monitoring the project.

    The development of the overall system requires precise modularization by the students and the interfaces must be clearly defined so that the integration of the various modules runs smoothly. The success of the project is ensured by comprehensive integration tests that check and validate the interaction of the modules.

    The students use various professional tools and platforms for communication / documentation and software development, including a document management system, planning tools, version control software and other applications for project planning and monitoring. Project-oriented time recording is also carried out in order to document progress transparently.

    The tasks are based on current developments in the healthcare sector and meet the specific requirements of medical informatics and medical technology. Attention is paid to compliance with relevant standards in order to ensure the quality and relevance of the solutions developed.

    Teaching methods

    Implementation of a software project in a team: In this module, students are responsible for independently drawing up a project schedule for the semester and planning and organizing their attendance dates. The lecturer acts primarily as the client (possibly in cooperation with a company) and also as an overarching, observing project manager who is available to the students as a contact person for problems and questions if necessary, but generally stays in the background to promote the students' independent work process.

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Presentation

    Requirements for the awarding of credit points

    • successful project work
    • successful presentation

    Applicability of the module (in other degree programs)

    Bachelor's degree in Medical Informatics

    Literature

    Muss von den Studierenden selbst in Bezug zum gewählten Thema der Projektarbeit ermittelt werden.

    Übergreifend:

    • Wissenschaftliches Arbeiten - Wissenschaft, Quellen, Artefakte, Organisation, Präsentation - Helmut Balzert, Christian Schäfer, Marion Schröder - W3L, 2. Aufl., 2011

    Projektarbeit
    • PF
    • 2 SWS
    • 10 ECTS

    • Number

      45194

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      0 h

    • Self-study

      150 h


    Learning outcomes/competences

    Through the project work, students learn the following skills, which prepare them for writing their later thesis and qualify them for starting their career:

    • Solving computer science-specific problems where possible in a business context by engineering a software/hardware solution (i.e. specifying requirements, weighing up and evaluating alternative solutions, modeling systems and ensuring quality) taking into account limited resources.
    • Conducting the work as a project (i.e. setting objectives and planning projects, pre- and post-calculation of the time required), and 
    • Production of the written paper using scientific working methods (e.g. literature research, correct citation) 
    • Evaluate the results of your own work
    • .
    • Ability to work in a team with developers and (where possible) users, especially: to present work results, to lead and moderate meetings and to resolve conflicts.
    • Dealing with practically relevant tasks
    • .

    For further details, see process description PB-PAAA (Annex IV).

     

    Contents

    The students have the right to suggest a project topic. The project should preferably be carried out outside the university or within the framework of a practice-oriented research project. Group work is desired.
    The specific knowledge directly required in the projects will be taught in block courses if necessary.
    Regular project meetings should give students the opportunity to acquire the above-mentioned teamwork skills by practicing them. In particular, quality assurance should be practiced by presenting results from analysis, design and implementation. The computer science knowledge, skills and abilities already acquired should be applied and consolidated and expanded in a problem-oriented manner.

    Teaching methods

    Seminar

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Project work with oral examination
    • Presentation

    Requirements for the awarding of credit points

    • successful project work
    • successful presentation

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Medical Informatics

    Literature

    Muss von den Studierenden selbst in Bezug zum gewählten Thema der Projektarbeit ermittelt werden.

    Übergreifend:

    • Wissenschaftliches Arbeiten - Wissenschaft, Quellen, Artefakte, Organisation, Präsentation - Helmut Balzert, Christian Schäfer, Marion Schröder - W3L, 2. Aufl., 2011

    Seminar (Inhalt)
    • PF
    • 2 SWS
    • 2.5 ECTS

    • Number

      45182

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    After successfully completing this module, students will be able to


    Knowledge and Understanding

    • Name and understand the content-related competencies corresponding to the respective focus of the seminar. (Note: Since the content varies, the placeholder competency for the specific subject knowledge is set here).

    Use, apply and generate knowledge

    • Use scientific methods to develop a presentation on the content focus.
    • Independently research and evaluate technical and scientific content.
    • structure and document information.
    • To write a scientific term paper.
    • Independently develop scientific texts.
    • Develop content relevant to the professional field.
    • Apply the skills they have learned in their studies and career.

    Communication and cooperation

    • Working in groups and interacting within groups.
    • Create presentations and present results.
    • Present and defend content in groups.

    Scientific self-image / professionalism

    • Structure scientific texts independently.

    Contents

    The seminars include topics that expand students' specialist academic skills. Students prepare a presentation on a selected special topic in business administration, computer science and/or business informatics and present the content. The topics are offered each semester with new, up-to-date content by all professors and lecturers and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Modern Supply Chain Management for Information Logistics, Business Simulation and Social Networks. The professional orientation of the seminars is strengthened by the use of lecturers from Business Studies with special qualifications in the subjects.

    Teaching methods

    Seminar

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Presentation

    Requirements for the awarding of credit points

    • successful presentation
    • regular participation in at least 80% of the attendance dates

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics

    Literature

    Literatur muss vom Studierenden selbst ermittelt werden.

    Übergreifend:

    • Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011

    Signal- und Bildverarbeitung für die Medizin
    • PF
    • 6 SWS
    • 5 ECTS

    • Number

      44452

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    The course deals with the development and analysis of systems that use signal and image processing methods in medicine. After successfully completing the course, students will have acquired the following skills:


    Knowledge (knowledge):
    - can name the successes and challenges of medical signal and image processing in the context of clinical radiology
    - know the stages of medical signal and image processing and can explain them
    - know the most important mathematical and algorithmic concepts of medical signal and image processing and can apply these in software codes
    - know examples of medical applications of image processing
    - know the basics of machine learning methods including deep learning for signal and image processing tasks

    Skills
    - can solve signal and image processing problems by combining the methods covered in the course (building an image processing pipeline)
    - can develop simple image processing applications using the programming system Matlab® or the programming language Java or Python and ImageJ
    - can evaluate developed signal and image processing pipelines
    - can plan, implement and present signal and image processing mini-projects in a team


    Competencies (personal and social skills)
    - can formulate ideas and proposed solutions orally and in writing
    - can solve tasks in exercises and practicals independently and present the results
    - can develop solutions cooperatively in the exercise and project phases
    - can cooperatively plan, distribute and jointly carry out tasks for solutions in the project phases
    - can argue in discussions in a goal-oriented manner and deal with criticism objectively
    - can present the results of group work together
    - can evaluate project results and formulate suggestions for improvement
    - can recognize and reduce misunderstandings between discussion partners

    Contents

    - Introduction and motivation: Clinical applications of digital signal and image processing and characterization of important medical image objects such as bones, vessels, tissue, tumors, etc.
    - Overview of the stages of medical signal and image processing (1D, 2D, 3D, 4D)
    - Introduction to a selected programming interface (practical course): Expansion of Matlab® knowledge
    - Digitization (sampling, quantization), structure and properties of medical image data
    - Signal and image pre-processing in the spatial domain
    - Signal and image pre-processing in the frequency domain, convolution theorem, sampling theorem
    - Segmentation of medical image data: thresholding methods, edge-oriented methods, area and volume growth methods
    - Quantitative image analysis, image recognition and classification
    - Image compression methods and the standard DICOM format for medical image data
    - Modern feature extraction, e.g. interest points
    - Registration
    - Introduction of deep learning for image classification

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written examination paper
    • examinations during the semester

    Requirements for the awarding of credit points

    • passed written examination
    • successful mini-project (project-related work)

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Handels, H.; Medizinische Bildverarbeitung; Vieweg+Teubner; 2. Auflage; 2009
    • Nischwitz, A. et al.; Computergrafik und Bildverarbeitung: Band II: Bildverarbeitung; Vieweg+Teubner; 3. Auflage, 2011
    • Bankman, I. et al.; Handbook of Medical Image Processing and Analysis; Academic Press; 2. Auflage; 2009
    • Gonzalez R. et al.; Digital Image Processing; Prentice Hall; 4. Auflage; 2018
    • Burger, W und Burge, M. J., Digitale Bildverarbeitung, Springer-Verlag, 3. Auflage, 2015 (auch elektronisch in der FH Bibliothek vorhanden)

    Computergrafik
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46809

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding

    After successful participation in the module:

    • the students have knowledge of the terminology of computer graphics and can use it correctly to describe graphics systems
    • can explain mathematical concepts, algorithms and data structures of computer graphics using examples

    Use, application and generation of knowledge

    After successfully completing the module, students will be able to:

    • apply mathematical concepts, algorithms and data structures of computer graphics to problems
    • construct scene graphs including transformations
    • Implement solutions for typical computer graphics problems using OpenGL and GLSL

    Contents

    Lecture

    • Introduction:
      Visual information processing and its applications, hardware and software of graphical systems
    • 2D graphics:
      Basic elements and fundamental algorithms, curves, transformations and clipping, raster conversion
    • 3D graphics:
      Basic elements, curves and surfaces, body modeling, scene graph and transformations, projection, visibility and occlusion, shader programming, lighting and shading, textures, ray tracing

    Internship

    • Graphics programming with C++, OpenGL and the OpenGL Shading Language (GLSL)

    Teaching methods

    • Lecture in interaction with the students incl. exercises based on practical examples
    • Practical course accompanying the lecture with the completion of programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    • Nischwitz, A., Fischer M., Haberäcker P., Socher G.: Computergrafik : Band I des Standardwerks Computergrafik und Bildverarbeitung; Springer Vieweg; 4. Auflage; 2019
    • Marschner, S., Shirley, P.: Fundamentals of Computer Graphics, 5th. ed., CRC Press, 2022
    • Hughes J.F., van Dam A., McGuire M., Sklar D.F., Foley J., Feiner S.K., Akeley K.: Computer Graphics principles and practice, 3rd ed., Addison-Wesley, 2013
    • Kessenich, J.; Sellers, G.; Shreiner,D.: OpenGL Programming Guide, 9th ed., Addison-Wesley, 2017

    Effiziente Algorithmen und Datenstrukturen
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46889

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    • Be able to describe basic algorithmic methods
    • .
    • Be able to assess problems in terms of their modeling possibilities and algorithmic complexity.
    • Be able to describe and implement efficient algorithms and data structures for selected basic problems.
    • Categorize algorithms with regard to their quality under different efficiency aspects.Know concepts and methods for solving combinatorial optimization problems and be able to apply them to a problem.Be able to check the correctness and efficiency of algorithms.

    Contents

    • Basics
      • O-notation
      • Graphs
    • Graph algorithms
      • Shortest paths
      • Minimal spanning trees
      • Flows in networks
      • Matchings
      • Tours
    • Algorithmic techniques
      • Divide and Conquer
      • Dynamic programming
      • Greedy algorithms
    • Optimization problems
      • Backtracking
      • Branch-and-bound
      • Approximation algorithms

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Solving practical exercises in individual or team work
    • Group work
    • Individual work
    • Presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor of Computer Science Dual
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics with practical semester
    • Bachelor of Medical Informatics Dual

    Literature

    • T. Cormen, C. Leiserson, R. Rivest, C. Stein: "Algorithmen - Eine Einführung", Oldenbourg, 4. Auflage, 2013
    • T. Ottmann, P. Widmayer: "Algorithmen und "Datenstrukturen", Spektrum Akademischer Verlag, 6. Auflage, 2017
    • G. Pomberger, H. Dobler: "Algorithmen und Datenstrukturen", Pearson Studium, 2008
    • R. Sedgewick, K. Wayne: "Algorithmen", Pearson Studium, 2014
    • R. Wanka: "Approximationsalgorithmen - Eine Einführung", Teubner, 2006
    • B. Vöcking, H. Alt, M. Dietzfelbinger, R. Reischuk, C. Scheideler, H. Vollmer, D. Wagner: "Taschenbuch der Algorithmen", Springer, 2008

    Fortgeschrittene Informationssicherheit
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46900

    • Language(s)

      en

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    The students are able to

    • apply methods, best practices and software tools relevant in practice for the development of secure software
    • independently evaluate various cryptographic methods as part of a software development project and select adequate cryptographic methods based on this.
    • independently develop software that uses cryptographic methods and systematically test the software.

    Contents

    • Java Cryptography Architecture and API
    • Legion of the Bouncy Castle Java Cryptography APIs
    • Block ciphers: AES, padding, block modes, use as stream ciphers
    • Stream ciphers: ChaCha20, generation of key streams
    • Password-based encryption/decryption
    • Key management
    • Message digests, MACs, key derivation functions
    • Asymmetric cryptography: DH, RSA, DSS, ECDSA
    • Methods for developing secure software: e.g.
      • Design principles according to Saltzer and Schroeder
      • Secure coding guidelines (Java)
      • Secure code review
      • Unit testing when using cryptography
      • Penetration testing with software tools
      • Best practices (OWASP Top 10, SAMM, ASVS)

    The language of instruction is English.

    C# can be used as an alternative to Java.

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Inverted teaching (inverted classroom)
    • Individual work
    • Project work accompanying the lecture with final presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Project-related work (100%)

    Requirements for the awarding of credit points

    • Successful project-related work

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • D. Hook und J. Eaves: Java Cryptography: Tools and Techniques, Leanpub, 2023
    • F. Long, D. Mohindra, R. C. Seacord, D. F. Sutherland und D. Svoboda: Java Coding Guidelines: 75 Recommendations for Reliable and Secure Programs, Addison-Wesley Professional, 2013
    • K. Schmeh: Kryptografie Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016
    • R. E. Smith: A Contemporary Look at Saltzer and Schroeder s 1975 Design Principles, IEEE Security & Privacy, 10(6), 20-25, 2012

    Adaptive Systeme
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46901

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successful participation in the module courses, students are able to ...

    Know and understand:

    • Recognize problems in which adaptive systems can be used to solve problems
    • to recognize that adaptive systems methods can be used to describe properties of technical, business and social systems and to analyse their behaviour.
    • to implement and, if possible, evaluate adaptive systems based on the models explained.
    • to recognize the limits of adaptive systems.

    Deployment, application and generation of knowledge:

    • Develop and analyze solutions to problems with adaptive systems
    • .
    • Use computational intelligence methods for the design of adaptive systems

    Contents

    • Basics and examples of adaptive and complex systems and their application (e.g. in the area of control systems, networks and the web)
    • Modeling of adaptation processes using various adaptive techniques
    • Theory and application of soft computing methods (e.g. evolutionary algorithms, particle swarm optimization, ant colony optimization, fuzzy logic, neural networks and modern machine learning methods) for system adaptation to (context) changes 
    • Application of data classification methods to decision support systems (e.g. rating systems, collaborative and social recommendation systems)
    • Selected current methods from the field of computational intelligence and adaptive systems

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Internship to accompany the lecture
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of  
    • 100% of the overall grade consists of a written examination (90-120 minutes) or oral examination (20-30 minutes) (according to the current examination schedule), in which students analyze application scenarios, explain various theoretical principles and apply them situationally 

    Requirements for the awarding of credit points

    passed written examination or passed oral examination (according to current examination schedule)

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science

    Literature

    • J. Schmidt, Chr. Klüver, J. Klüver, Programmierung naturanaloger Verfahren, Vieweg+Teubner Verlag (2010)
    • R. Kruse, C. Borgelt, F. Klawonn, C. Moewes, G. Ruß, M. Steinbrecher, Computational Intelligence, Zweite Auflage, Vieweg+Teubner Verlag (2015)
    • W.-M. Lippe, Soft-Computing, Springer Verlag (2005)
    • A. Kordon, Applying Computational Intelligence, Springer Verlag (2010)
    • I. Witten, E. Frank und M. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 4. Auflage, Morgan Kaufmann (2017), elektronische Version im Intranet verfügbar
    Weitere Literatur wird in der Vorlesung bekannt gegeben.
    Weitere aktuelle Literatur wird in der Vorlesung bekannt gegeben

    Anerkannte Wahlpflichtprüfungsleistung
    • WP
    • 0 SWS
    • 5 ECTS

    • Number

      46991

    • Duration (semester)

      1


    Anerkannte Wahlpflichtprüfungsleistung
    • WP
    • 0 SWS
    • 5 ECTS

    • Number

      46992

    • Duration (semester)

      1


    Anerkannte Wahlpflichtprüfungsleistung
    • WP
    • 0 SWS
    • 5 ECTS

    • Number

      46993

    • Duration (semester)

      1


    Angewandte Logiken
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46817

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    • Completers of the module have mastered advanced formal logic concepts in computer science and are able to transfer concrete classical and non-classical logics, logic concepts and methodologies to various computer science problems, adapt them to the respective needs and finally apply them in practice.
    • In particular, students will master the basics of formal logic modeling of dynamic processes and their applicability as well as techniques of formal specification and verification of models.
    • The students can apply these skills across disciplines.

      Self-competence:

      • The participants are able to independently deal with current research papers on formal logic modeling and verification in computer science and to understand the core statements.

      Social skills:

      • The participants are able to present formal-logical topics and questions in a didactic manner in presentations and written papers. In particular, they are able to present complex formal-logical issues at different levels of granularity (from conveying the pure underlying idea to formulating the exact mathematical facts).
      • The participants are able to lead discussions on scientific issues (in particular with regard to the applicability of the content taught to their respective field of study).The participants understand the relevance of the content taught for their field of study and are able to communicate this relevance adequately.

         

    Contents

    The event includes the following topics:

    • Classical concepts of modal logic (such as possibility and necessity) and their relevance in computer science
    • Syntax and semantics of classical modal and temporal logics (such as CTL*, CTL and LTL) and their applications
    • Formal-logical specification and modeling of computer science processes using possible-world semantics
    • (Automated) verification of modeled processes using model checking methods and their applications in practice
    • Syntax and semantics of epistemic logics (such as belief sets and epistemic modal logic) and their relevance for computer science
    • Exemplary application of the topics learned: depending on the interests and professional background, various example applications can be chosen such as Formal Hardware Verification , Modeling Dynamic Processes , Concurrency , etc.
    • Sensible intensional / propositional logics and their applications in modern computer science applications
    • Relevance of logics in the applications of artificial intelligence

    Teaching methods

    • Lecture in seminar style, with blackboard and projection
    • Exercise to accompany the lecture

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Presentation [scope: 50%] (45 minutes)
    • Written exam [scope: 50%] (60 minutes)

    Requirements for the awarding of credit points

    • Passed presentation
    • Passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    • Hughes und Cresswell A New Introduction To Modal Logic, Routledge Chapman & Hall,
    • Kropf Introduction to Formal Hardware Verification, Springer-Verlag Berlin and Heidelberg, 1999
    • Chagrov und Zakharyaschev Modal Logic, Oxford University Press, 1997
    • Gardenfors - Knowledge in Flux: Modeling the Dynamics of Epistemic States (Studies in Logic), College Publications, 2008
    • Bab - Epsilon_mu-Logik - Eine Theorie propositionaler Logiken, Shaker Verlag Aachen, 2007

     

    Ausgewählte Aspekte der Medizinischen Informatik 1
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46131

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    This module combines courses on various computer science topics that are not offered regularly. The contents and competencies are published each semester in an additional document.
    The competencies are derived from the published supplementary document for the specific course.

    Contents

    The contents can be found in the published supplementary document for the specific event.

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Lecture in seminar style, with blackboard and projection
    • exercise accompanying the lecture
    • Internship accompanying the lecture

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Written written examination
    • project-related work with documentation and presentation followed by an oral examination
    • Oral examinations
    • Homework
    • presentations 

    Requirements for the awarding of credit points

    Passed exam

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    siehe Zusatzdokument zur konkreten Veranstaltung

    Ausgewählte Aspekte der Medizinischen Informatik 2
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46132

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    This module combines courses on various computer science topics that are not offered regularly. The contents and competencies are published each semester in an additional document.
    The competencies are derived from the published supplementary document for the specific course.

    Contents

    The contents can be found in the published supplementary document for the specific event.

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Lecture in seminar style, with blackboard and projection
    • exercise accompanying the lecture
    • Internship accompanying the lecture

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Written written examination
    • project-related work with documentation and presentation followed by an oral examination
    • Oral examinations
    • Homework
    • presentations 

    Requirements for the awarding of credit points

    Passed exam

    Literature

    siehe Zusatzdokument zur konkreten Veranstaltung

    Ausgewählte Aspekte der Medizinischen Informatik 3
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46133

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Courses on various computer science topics that are not offered regularly are summarized in this module. The contents and competencies are published each semester in an additional document.
    The competencies are derived from the published supplementary document for the specific course.

    Contents

    The contents can be found in the published supplementary document for the specific event.

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Lecture in seminar style, with blackboard and projection
    • exercise accompanying the lecture
    • Internship accompanying the lecture

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Written written examination
    • project-related work with documentation and presentation followed by an oral examination
    • Oral examinations
    • Homework
    • presentations 

    Requirements for the awarding of credit points

    passed exam

    Applicability of the module (in other degree programs)

     
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    siehe Zusatzdokument zur konkreten Veranstaltung

    BWL
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      45281

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding:

    • Students understand the basic concepts of business administration and their relevance to the field of IT.
    • They know the historical development of Business Studies as well as the legal foundations of entrepreneurial activity and can distinguish between correct and incorrect statements.
    • They know the differences between cost centers, cost types and cost units.
    • They understand the structure and organization of companies and the tasks of individual company divisions.

      Use, application and generation of knowledge:

      • Students analyze the business and legal consequences of operational decisions
      • .
      • They are proficient in cost accounting methods, in particular cost types, cost centers and cost unit accounting.
      • You can use tools and techniques for costing and calculate the individual, relevant influencing factors.You will be able to create a cost accounting sheet (BAB) and make cost-conscious decisions.
      • You will use costing techniques to evaluate projects and investments from a business studies perspective.
      • They understand materials management, warehousing, production management and sales management and can optimize operational processes.
      • You will apply business management methods such as ABC analysis and network planning techniques.They are familiar with company foundation processes, company forms and aspects of capital increases.They combine business knowledge with IT-supported tools such as Excel and MS Project.

        Communication and cooperation:

        • The students work in groups on business management tasks and learn about the requirements of team processes.
        • They present business studies and discuss operational decision-making processes.

        Scientific self-image / professionalism:

        • Students reflect on business management decisions and their impact on companies
        • .
        • They are able to critically scrutinize Business Studies concepts and make sound business decisions.

    Contents

    • Historical development of Business Studies
    • Legal foundations
    • Operation and company, structure, organization and task of company divisions
    • Procurement management
    • Materials and warehouse management
    • Production management
    • Sales management
    • Business accounting, calculations and cost accounting, BAB
    • ABC analysis and project management (network planning technique)
    • Company formation, types of company, capital increase

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Group work
    • Individual work
    • Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Philip Junge: BWL für Ingenieure, Springer Verlag 2012
    • Kruse/Heun : Betriebswirtschaftslehr, Winklers Verlag
    • Deitermann, M., Schmolke, S., IKR mit Kosten- und Leistungsrechnung, Winklers Verlag

    Componentware
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46808

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Introduction to component-based software development and application of what has been learned in practical examples based on EJB.

    Technical and methodological competence:

    • Knowing and defining the concept of components
    • Understanding the challenges of distributed systems
    • Knowing solution approaches with and without middleware
    • Know typical problems in enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
    • Modeling distributed systems with UML
    • Understanding the difference between specification and its realization
    • Understanding the EJB specification
    • Applying EJB knowledge with the glassfish application server
    • Develop an independent solution as part of a project

    Interdisciplinary methodological competence:

    • Developing a project from any application domain

    Social skills:

    • Systematically work on problems of medium to high complexity in a team
    • Develop an EJB solution in a cooperative and collaborative team
    • Document an EJB solution in a cooperative and collaborative team

    Contents

    • General basics of component technology (motivation, definitions, goals,...)
    • Fundamental terms and challenges of enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
    • Software architecture principles and concepts for defining software components and platforms
    • Concept of the application server
    • Stateless session beans
    • Stateful session beans
    • Singleton session beans
    • Message Driven Beans
    • Timer Services
    • Entity Manager and Persistent Entities
    • Transaction management
    • Characteristic features of component-based systems

    Teaching methods

    • Lecture in seminar style, with blackboard and projection
    • Exercise to accompany the lecture
    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture
    • project work accompanying the lecture with final presentation
    • Exercises or projects based on practical examples

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Project work with oral examination
    • Presentation
    • Semester-accompanying study achievements (bonus points)

    Requirements for the awarding of credit points

    • passed oral examination
    • successful project work
    • successful presentation

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    • Oliver Ihns et. al.: EJB 3.1 professionell. Grundlagen- und Expertenwissen zu Enterprise JavaBeans 3.1 inkl. JPA 2.0, dpunkt.verlag GmbH, Auflage: 2., 2011
    • Jan Leßner, Werner Eberling: Enterprise JavaBeans 3.1: Das EJB-Praxisbuch für Ein- und Umsteiger, Carl Hanser Verlag GmbH & CO. KG; Auflage: 2, 2011
    • Clemens Szyperski, Dominik Gruntz and Stephan Murer: Component software. Beyond object-oriented computing, Pearson, 2nd Edition, 2002
    • CBSE-Proceedings: nth International Symposium on Component-Based Software Engineering

    Data Mining in Industrie und Wirtschaft
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46843

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

     

    Students master important methods and algorithms of modern data analysis for recognizing patterns and structures in large data sets. In particular, they are familiar with the three phases of pre-processing, analysis and evaluation of the data mining process. They will be able to select and apply suitable data analysis methods for specific applications in industry and Business Studies and use them to support decision-making.

    Technical and methodological competence:

    • Students have a sound knowledge of the data analysis methods covered.
    • The students know which method is suitable for which questions and data types and can classify and interpret analysis results.Students can carry out independent analyses of data sets using both Excel and special software (e.g. R, JMP, ...).

    Social skills:

    • The students can analyze data sets from practice in teamwork using the methods of the course and present the results to the plenum.

    Contents

     

    • Phases of data mining
    • Data, relations and data preprocessing
    • Multiple regression
    • Cluster analysis
    • Classification methods
    • Association analysis
    • Outlier detection

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Processing programming tasks on the computer in individual or team work
    • Exercises or projects based on practical examples

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Project work with oral examination
    • Examinations during the semester

    Requirements for the awarding of credit points

    • passed oral examination
    • successful project work
    • successful mini-project (project-related work)

    Applicability of the module (in other degree programs)

    • Bachelor of Medical Informatics
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Business Informatics
    • Bachelor of Computer Science

    Literature

     

    • Cleve, J., Lämmel, U. (2020), Data Mining, 3. Auflage, De Gruyter, Berlin/Boston
    • Runkler, A. (2015) Data Mining: Modelle und Algorithmen intelligenter Datenanalyse, 2. Auflage, Springer VS, Wiesbaden.
    • Hastie, T., Tibshirani, R., Friedmann, J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2. Auflage, Springer, New York

    Datenbanken 2
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46812

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successful participation in the module courses and completion of the course-related project, students will be able to design and implement database applications with relational databases and optimize their performance. Subject and methodological skills:

    •  Model object-oriented extensions using EER models and implement them in relational databases.
    • Discuss the limitations of the relational database model using examples.
    • Implement complex user views and stored procedures for exemplary application scenarios.
    • Design and implement database applications in Java.
    • Explain the 5-level model of a database management system.
    • Explain concepts of storage and access management.
    • Use examples to apply the methods of access optimization and transaction management.
    • Evaluate performance optimization options and apply SQL tuning methods.

      Social skills:

      • Developing, creating, communicating and presenting database applications in small groups

       

    Contents

    Database implementation

    • Storage management
    • Logical and physical access optimization
    • Transaction management
    • Distributed databases
    • Performance optimization and SQL tuning

    Development of database applications

    • Data modeling (EER model and logical design of object-oriented concepts)
    • Limitations of the relational model
    • Ensuring data integrity and data protection (view hierarchies, stored procedures, triggers)
    • Conception, design and implementation of database applications in JAVA

    Teaching methods

    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture
    • Processing programming tasks on the computer in individual or team work
    • Active, self-directed learning through Internet-supported tasks, sample solutions and accompanying materials
    • Exercises or projects based on practical examples
    • The lecture is offered as a video
    • Inverted teaching (inverted classroom)

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a written exam (60-90 minutes) and coursework during the semester.
    In the written exam, students should demonstrate basic knowledge of theoretical concepts, database architecture, performance optimization and development of database applications and demonstrate their skills in solving small application problems.

    Through semester-long examinations (project-related work), students should design, develop, implement and present a database application for a self-chosen application scenario.

    Requirements for the awarding of credit points

    The performances are graded and must be passed with a total grade of 4.0. The performances consist of:
    • passed written examination (80%)
    • successful mini-project (project-related work)  (20%)

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • R. Elmasri, S. Navathe, Grundlagen von Datenbanksystemen, 2009
    • A. Kemper, A. Eickler, Datenbanksysteme (Eine Einführung), 2015
    • G. Saake, K.-U. Sattler, A. Heuer, Datenbanken Implementierungstechniken, 2011
    • R. Niemiec, Oracle database 12c release 2 performance tuning tips & techniques, 2017
    • R. Panther, SQL-Anfragen optimieren, 2014

    Datenethik und digitale Verantwortung
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46818

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successful participation in the module courses and completion of the project work, students are able to ...
     

    • recognize and apply data ethics principles and assess them in complex contexts
    • to reflect on and classify data science methods in the context of ethical aspects
    • to be able to apply methods, concepts and legal principles of data protection in the context of information technology
    • Analyze and compare case studies of relevance to data ethics
    • Evaluate overall concepts for algorithms / software systems and data analysis

    Contents

    Introduction to data protection and data ethics
    • Definitions and basics.
    • Introduction to data ethics principles such as fairness, transparency and responsibility.
    • Historical context and examples from practice.
    Data ethics basics
    • Principles of ethics (e.g. utilitarianism, deontology) in the data context.
    • Analysis of case studies, e.g. algorithmic bias in AI systems.
    Data protection concepts and legal frameworks
    • Legal basics (introduction to the GDPR, AI Act and its main principles)
    • Identification and evaluation of processed personal data.
    • Privacy by Design and Privacy by Default.
    • Creation of data protection declarations.
    Methods of data science and ethical reflection
    • Methods for the ethical design of data science projects, e.g. EDAP Ethical Deliberation in Agile Processes or Data Ethics Canvas
    • Case studies with relevance to data ethics (topics such as facial recognition, surveillance systems, healthcare).
    • Reflection on data protection problems and discrimination through algorithms, as well as possible solutions.
    Technologies and system development
    • Encryption, anonymization and other technical data protection measures (possibilities and limits)
    • Use of international IT services in compliance with data protection regulations.
    • Development of algorithms and software systems in compliance with data protection and ethics.

    Teaching methods

    • seminar-style teaching with flipchart, smartboard or projection
    • Internship accompanying project work
    • Project work in teamwork
    • Project work with final presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • Seminar elaboration and presentation of a team
    • Project work with final presentation

    Requirements for the awarding of credit points

    • successful project work
    • successful oral presentation
    • successful elaboration and presentation of a topic

    Applicability of the module (in other degree programs)

    Bachelor of Computer Science

    Literature

    • AI Act, https://artificialintelligenceact.eu/de/
    • The Great Hack (Cambridge Analyticas großer Hack), 2019. Directed by Amer, K. and Noujaim, J.: Netflix.
    • Datenethikkommission, Bundesministerium der Justiz und für Verbraucherschutz (2018) Empfehlungen der Datenethikkommission für die Strategie Künstliche Intelligenz der Bundesregierung.
    • Thomas A. Degen, Jochen Deister, et al. (2021), IT- und Datenschutz-Compliance für Unternehmen: Leitlinien und Anwendungsfälle - Cloud, Social Media, Scrum, IoT, KI, Mobilitätsdaten: IT-Projekte und Leitlinien nach DSGVO
    • Flick, C. (2016) 'Informed consent and the Facebook emotional manipulation study', Research Ethics, 12(1), pp. 14-28.
    • Gesellschaft für Informatik e.V. 2018. Technische und rechtliche Betrachtungen algorithmischer Entscheidungsverfahren. In: Studien und Gutachten im Auftrag des Sachverständigenrats für Verbraucherfragen (ed.). Berlin: Sachverständigenrat für
    Verbraucherfragen.
    • o.V. (2021) Ethischer Kompass für Informatik-Fachleute - Basierend auf den ethischen Leitlinien der Gesellschaft für Informatik. Bonn: Gesellschaft für Informatik e.V.
    •  Hochrangige Expertengruppe für KI (HEG-KI) (2019) Ethik-Leitlinien für eine vertrauenswürdige KI. Brüssel: Europäische
    Kommission.
    • Müller, L.-S. and Andersen, N. (2017) 'Denkimpuls Digitale Ethik: Warum wir uns mit Digitaler Ethik beschäftigen sollten – Ein Denkmuster', Initiative D21. http://initiatived21.de/app/uploads/2017/08/01-2_denkimpulse_ag-ethik_digitale-ethik-eindenkmuster_
    final.pdf (Accessed 28. November 2021).
    • A. Pretschner, N. Zuber, J. Gogoll, S. Kacianka and J. Nida-Rümelin(2021): Ethik in der agilen Software-Entwicklung in: Informatik Spektrum 2021 Vol. 2021 Issue 44 Pages 348-354
    • Spiekermann, S. 2018. Kann man Ethik standardisieren? In: Köver, C. and Dachwitz, I. (eds.) Netzpolitik-Podcast Folge 161.
    • Strecker, S. 2019. Maschinenethik - Gespräch mit Oliver Bendel. In: Strecker, S. (ed.) Perspektiven | Wirtschaftsinformatik- Podcast
    • Europäische Union, Charta der Grundrechte der Europäischen Union, 2019
    Europäische Union, Verordnung (EU) 2016/679 des Europäischen Parlaments und des Rates vom 27. April 2016 zum Schutz natürlicher
    Personen bei der Verarbeitung personenbezogener Daten, zum freien Datenverkehr und zur Aufhebung der Richtlinie 95/46/E125
     

    ERP 1 (Standardsoftware)
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46828

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successfully completing the module, students will be able to:

    • Classify and differentiate between individual, standard and industry software.
    • Name the advantages and disadvantages of standard software.
    • evaluate the current market situation.
    • Name criteria for the selection of standard software.
    • apply a systematic approach to the selection of standard software.
    • Be familiar with procedure models for the introduction of standard software.
    • distinguish between different customization options for standard software and evaluate their respective consequences.
    • to gain an overview of the complexity of business processes in integrated systems.
    • design and implement functional enhancements to standard software.
    • understand and apply the importance of communication, conflict and team skills in implementation and customization projects.
    • to recognize and understand social problems of an ERP implementation and to deal sensitively with their consequences.
    • understand the requirements of different job profiles in the ERP environment (in particular sales, consulting, project management, application development)
    •  

    Contents

    • General basics (definition of terms, historical development, ... )
    • Standardization concept (classification and differentiation from in-house development, degree of coverage, ... )
    • Integration aspects (technical and organizational integration, examples and consequences, ... )
    • Business management components (financial accounting, HR, logistics, production, ... )
    • selection process (market overview and breakdown, selection criteria, decision-making process, ... )
    • Introduction of an ERP system (project approach, implementation strategies, procedures)
    • Technical basics (system structure, hardware platforms and supported databases, ... )
    • Installation, maintenance and operation of an ERP solution
    • Adaptations to standard software (types of adaptations, their delimitation and consequences, ... )
    • Integrated development environments and programming languages
    • Inhouse developments (functional expansion of an ERP system in practical exercises using a mini-project)

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Processing programming tasks on the computer in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • The module examination consists of a written exam in which students are asked to recall basic knowledge from the lecture and remember the knowledge, in particular technical terms. Review questions on the respective chapters serve as preparation. In addition, they should be able to apply this knowledge to specific questions from practice and explain it if necessary.
      Duration: 90 minutes
       
    • As optional coursework (bonus points) during the semester, a practice-oriented case study must be completed and a small extension developed under supervision. The practical knowledge and skills can then be deepened independently in a further (mini) project and applied as a transfer achievement.
       

    Requirements for the awarding of credit points

    passed written exam (at least 50% of the maximum achievable points)

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science

    Literature

    • Skript zur Vorlesung (Hesseler, M.)
    • Hesseler, M.; Görtz, M.; Basiswissen ERP-Systeme ; w3l-Verlag; Bochum; 2007;
    • Ergänzende Literaturempfehlungen (nicht zwingend erforderlich):
      • Allweyer, T.; Geschäftsprozessmanagement ; w3l-Verlag; Bochum; 2005;
      • Hesseler, M. und Rösel, C.; ERP-Übungsbuch: Entwicklung einer einfachen Fuhrpakrverwaltung in Microsoft Dynamics NAV ; Books on Demand; Norderstedt; 2010;
      • Hesseler, M. und Görtz, M.; ERP-Systeme im Einsatz ; w3l-Verlag; Herdecke; 2009;

    IT-Management von Gesundheitseinrichtungen
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46871

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      90 h

    • Self-study

      60 h


    Learning outcomes/competences

    Subject and methodological competence:
    After completing the module, students will be able to describe project management according to Ammenwerth. They will be able to carry out project management in a project and thus apply the theory in a specific case, going through all the relevant phases of project management. In addition, students will be able to name the key documents and their significance and create/process them as part of a project.
    Among other things, students are able to

    • to name the phases of project management according to Ammenwerth and to apply them to their own IT project in the form of a valid project plan
    • to reflect and differentiate the contents of strategic, tactical and operational project management
    • to name the special features of IT management in the healthcare sector and apply them analytically using examples
    • show the connection between IT management and process optimization
    • Conduct an as-is analysis of a given scenario and, based on this, carry out the management of a project
    • to name the essential documents in the context of project management and to create/edit them in the context of a project
    Social skills:
    • How to deal with users in the medical field
    • Working in a team
    Professional field orientation:
    • You will get to know a hospital information system
    • You will learn about the tasks of an IT manager in a hospital (CIO / CDO)
    • You will carry out a project and thus gain initial experience in project management

    Contents

    • Strategic, tactical and operational project management
    • Phases of project management
    • Project management tasks, e.g: Effort estimation, risk management, system specification, evaluation, completion (documentation)
    • From corporate strategy to IT strategy
    • IT as a competitive factor
    • Basics of the procurement of IT systems
    • IT as a medium for process optimization
    • Internship: Implementation project from the tactical management of an HIS as well as complete project documentation

    Teaching methods

    • Seminar-style lecture, with blackboard and projection
    • Processing exercises during the lecture, possibly on the computer in individual or team work
    • Active, self-directed learning through the use of electronic learning materials
    • Project work in a team with presentation
    • Excursion

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    semester-long project-related work with documentation and presentation incl. discussion, duration of presentation incl. discussion: 30 minutes

    Requirements for the awarding of credit points

    passed semester-long project-related work with documentation and presentation including discussion, with a grade of 4.0 or better

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Medical Informatics Dual

    Literature

    • Ammenwerth, E., & Haux, R. (2005). IT-Projektmanagement in Krankenhaus und Gesundheitswesen: einführendes Lehrbuch und Projektleitfaden für das taktische Management von Informationssystemen; mit 65 Tabellen. Schattauer Verlag.
    • Bachmann, W. (2009). Praxishandbuch IT im Gesundheitswesen: Erfolgreich einführen, entwickeln, anwenden und betreiben. Hanser Verlag.
    • Bea, F. X., Scheurer, S., & Hesselmann, S. (2020). Projektmanagement. utb GmbH.
    • Burghardt, M. (2012). Projektmanagement: Leitfaden für die Planung, Überwachung und Steuerung von Projekten. John Wiley & Sons.
    • Debatin, J. F., & Gocke, P. (Eds.). (2015). IT im Krankenhaus: Von der Theorie in die Umsetzung. MWV.
    • Guide, P. B. (2017). A Guide to the Project Management Body of Knowledge 6th Edition. Project Management Institute, Inc.
    • Kerzner, H. (2025). Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons.

    IT-Servicemanagement
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46905

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Transfer of basic knowledge regarding the importance and use of IT service management in the company. Theoretical knowledge of the five phases and their processes, roles and functions of the IT Infrastructure Library (ITIL) lifecycle model. Consolidation and practical application of previously acquired specialist knowledge using practical examples.

    Technical and methodological competence:

    • Distinguish between IT management and IT service management
    • Name reasons and objectives for using ITIL
    • Differentiate between the different phases of the ITIL lifecycle
    • Use case studies to deepen the knowledge gained and develop your own solutions in the ITIL environment
    • Designing and implementing your own ITIL implementation scenarios in example companies
    • Transfer of acquired knowledge and comparison with other reference/framework models

    Interdisciplinary methodological competence:

    • Selecting suitable communication structures for service and support processes/structures
    • Systematic prioritization of activities and projects
    • Knowing error cultures (human factor in stressful situations)
    • Systematic use of IT key figures to measure target achievement

    Professional field orientation:

    • Knowledge of the requirements of different job profiles in the IT service management environment (service owner, service manager, process owner, process manager, etc.)
    • Knowledge of IT processes in the context of IT service management
    • Knowing roles and responsibilities within IT service management
    • Selecting and using suitable models, concepts and tools

    Contents

    • IT management and business service management (BSM) basics
    • IT service management (ITSM) basics
    • Concepts and methods of IT service management
    • ITIL basics and history
    • ITIL (IT Infrastructure Library) V3 2011
    • Service strategy (Service Strategy)
    • Service design (Service Design)
    • Service Transition (Service Transition)
    • Service Operation (Service Operation)
    • Continuous Service Improvement
    • .
    • ISO/IEC 20000 and other ITSM reference models or reference models for IT service provision

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Project work accompanying the lecture with final presentation
    • Case studies
    • role-playing games

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written examination paper
    • examinations during the semester

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Software and Systems Engineering (dual)

    Literature

    • Beims, M.; IT-Service Management mit ITIL®, ITIL® Edition 2011, ISO 20000:2011 und PRINCE2® in der Praxis; 3. Auflage; Dr. Carl Hanser Verlag; 2012
    • Buchsein, R., Victor, F. Günther, H., Machmeier, V.; IT-Management mit ITIL® V3: Strategien, Kennzahlen, Umsetzung; 2. Auflage; Vieweg; Wiesbaden; 2008
    • Olbrich, Al.; ITIL kompakt und verständlich; 4. Auflage; Vieweg; Wiesbaden; 2006
    • Victor, F., Günther, H.; Optimiertes IT-Management mit ITIL; 2. Auflage; Vieweg; Wiesbaden; 2005
    • Zarnekow, R., Fröschle, H.-P.; Wertorientiertes IT-Servicemanagement: HMD - Praxis der Wirtschaftsinformatik (Heft 264); dpunkt Verlag; Heidelberg; 2008.

    Informations- und Business Performance Management
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46909

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding competence (professional competence)
    The students
    - know and understand central business and analytical concepts such as strategic alignment, document management, balanced scorecard, key performance indicator systems and predictive modeling and can classify their significance for analytical information systems,
    - recognize and explain the core concepts of the information supply chain, multidimensional modeling and the technical architectures of MOLAP, ROLAP and in-memory systems,
    - have a basic understanding of the concepts of data warehousing, data mining and big data processing,
    - understand advanced business management methods such as planning and budgeting and can explain their requirements for analytical IT systems,
    - know lifecycle models, reference models and modeling languages in the context of analytical applications and can classify them systematically,
    - can name and distinguish information architectures and evaluate them with regard to their areas of application.
    Skills (methodological and application competence)
    The students are able to
    - derive requirements from business methods and translate them into technical concepts of analytical applications,
    - develop and analyze multidimensional models and prepare them for reporting and analysis purposes,
    - Build reports, dashboards and analysis models from raw data and define suitable KPI structures,
    - Select lifecycle models such as Kimball, Inmon or CRISP-DM and apply them to a specific business intelligence project,
    - design and implement a small BI system in a team and evaluate it in terms of data quality, modeling and analytical benefits,
    - compare technical and conceptual alternatives of analytical architectures and make a well-founded selection.
    Social competence
    The students
    - work constructively, coordinated and goal-oriented in project teams,
    - communicate analysis results to the right audience and actively contribute to joint problem solving,
    - take responsibility for subtasks and support collaborative work processes as part of the semester-long project.
    Self-competence
    The students
    - reflect on their modeling, analysis and architecture decisions and can justify them professionally,
    - develop an awareness of the importance of data quality, transparency and traceability in analytical systems,
    - organize their work along lifecycle models and apply basic principles of project management independently.

    Contents

    • Overview and introduction
    • Chapter I
      • Information and decision theory
      • Information supply chain
      • Business signals
      • Operational and analytical applications
      • Balanced scorecard
    • Chapter II
      • Accounting, controlling, strategic planning
      • Extraction, transformation, loading (ETL)
      • Concept of the data warehouse
      • Multidimensional modeling
    • Chapter III
      • Predictive analytics, data mining methods and applications
    • Chapter IV
      • Big data and document management
    • Chapter V
      • Multidimensional business applications
      • OLAP analysis
      • Business planning
      • Group consolidation
    • Chapter VI
      • Case studies of analytical applications
    • Chapter VII
      • Strategic Business and IT Alignment
      • Lifecycle models for information management projects

    Semester-accompanying group project:
    Development of a reporting system for standard and OLAP reports based on tourism market research data using Microsoft SQL Business Intelligence Studio with the following sub-steps:

    • Understanding the question
    • Understanding the data
    • Processing the data
    • Modeling
    • Validation
    • Application

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture
    • Group work
    • Concluding presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • graded written examination 75% - 60min
    • graded semester-accompanying coursework 25% - compulsory attendance (two absences are tolerated, otherwise the semester-accompanying coursework will be reduced proportionately on the basis of the attendance dates) Group project (target number of three participants per group) over 8 weeks of 90min + acceptance interview 20min

    Requirements for the awarding of credit points

    • passed written exam
    • successful acceptance interview

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Bashiri, I., Engels, C., Heinzelmann, M., Strategic Alignment, Springer, 2010.
    • Cameron, S., SQL Server 2008 Analysis Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2620-0.
    • CRISP-DM, 1.0 step-by-step data mining guide, CRISP-DM consortium, 1999, (abgerufen am 25.11.2010) http://www.crisp-dm.org/download.htm.
    • Engels, C., Basiswissen Business Intelligence, W3L Verlag, Witten 2009.
    • Heinrich, Lutz J.: Informationsmanagement. Seit 1985 im Oldenbourg Wissenschaftsverlag, München / Wien, 8. Aufl. 2005, 9. Aufl. 2009 (1. bis 3. und ab 8. Aufl. mit Ko-Autor), ISBN 3-486-57772-7.
    • Jiawei Han, M.Kamber, Data Mining: Concepts and Techniques, http://www.cs.sfu.ca/~han/bk/.
    • Robert S. Kaplan, David P. Norton: Balanced Scorecard. Strategien erfolgreich umsetzen. Stuttgart 1997, ISBN 3-7910-1203-7.
    • Kemper et.al., Business Intelligence, Vieweg, 3. Auflage, 2010, ISBN 978-3-8348-0719-9.
    • Kimball, R. et. al., The Kimball Group Reader, Wiley, 2010.
    • Kimball, R., Caserta J., The Data Warehouse ETL Toolkit, Wiley, 2004.
    • Krcmar, H.: Informationsmanagement. 6. Auflage, Springer, Berlin et al., 2015, ISBN 978-3-662-45862-4
    • Misner, S., SQL Server 2008 Reporting Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2647-2.
    • Mitchell, T., Machine Learning, McGraw Hill, 1997.
    • Scheuch, R., Gansor, T., Ziller, C: Master Data Management: Strategie, Organisation, Architektur, dpunkt.verlag, 2012.
    • Plattner, H., Zeier, A.: In-Memory Data Management: An Inflection Point for Enterprise Applications, Springer, Berlin, 2011.

    Kooperative Systeme
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46912

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding

    • Students know the basics of social groups and essential categorizations of support by technical systems
    • Students understand the importance and effects of IT support for groups and communities

    Use, application and generation of knowledge

    • The students are able to select, adapt and introduce concrete systems for studying on site and working in groups by comparing and analyzing
    • The students design cooperative systems based on the categories, technologies and design principles covered
    • The students apply learned concepts of group work in an interdisciplinary manner
    Communication and cooperation
    • The students work on a term paper and presentation as group work and thus practise their social skills
    • .
    • The students examine and evaluate concrete cooperative systems in changing social constellations in work assignments in the seminar part
    • The students apply the concepts learned in this course on the topic of groups and the group support tools discussed

    Scientific self-image / professionalism

    • The students assess the significance of cooperative systems for the IT landscape of organizations, companies and communities

    Contents

    1. Basic concepts of cooperative systems
    2. Basic concepts of distributed systems
    3. Concurrency control & synchronization
    4. Awareness and design of multi-user interfaces
    5. Project work
    6. Community support and social networks
    7. Knowledge management in groups & organizations

    Teaching methods

    seminar-style lecture with presentations, small group work and assignments

    Participation requirements

    Admission requirements for the examination: 60 ECTS credit points from examinations in
    semesters 1 and 2.

    Forms of examination

    • Homework and
    • Presentation
    or
    • oral examination

    Requirements for the awarding of credit points

    • successful term paper and
    • successful presentation
    or
    • passed oral examination

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    • Borghoff, U.M.;  Schlichter, J.H. (1998): Rechnergestützte Gruppenarbeit - eine
      Einführung in verteilte Anwendungen. Springer, 2., vollst. überarb. und erw. Aufl.
    • Gross, T.; Koch, M. (2007): Computer Supported Cooperative Work. München: Oldenbourg.
    • Haake, J. M.; Schwabe, G.; Wessner, M. (Hrsg.) (2012): CSCL-Kompendium. München: Oldenbourg Verlag, 2. Auflage.
    • Schwabe, G.; Streitz, N.; Unland, R. (2001): CSCW-Kompendium: Lehr- und Handbuch Zum Computerunterstützten Kooperativen Arbeiten.Heidelberg: Springer.

    Mensch Computer Interaktion
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      43081

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    The course teaches the basics of user interfaces for efficient cooperation and interaction between humans and computers. In this context, both physiological and psychological aspects of human information processing are covered. Furthermore, software ergonomics is introduced as a scientific field that deals with the design of human-machine systems. Furthermore, the effects on concepts and implementations of software systems and user interfaces are examined and discussed.

    Technical and methodological competence:

    • Observation of the basic learning and action processes when using software
    • Knowledge of the standard operating elements for WIMP interfaces
    • Name the most important standards, laws and guidelines on SW ergonomics
    • Fundamental evaluation of the ergonomics of user interfaces based on these regulations
    • Mapping the activities in the user-centered design process to case studies
    • Basic knowledge of the most important usability engineering tools and their application in case studies

    Interdisciplinary methodological competence:

    • Knowledge of simplified action process models

    Social skills:

    • Observation, assessment and evaluation of communication situations
    • Working on tasks in alternating small groups (2-4 students each)

    Professional field orientation:

    • Interdisciplinarity of user experience design
    • Application of simple usability engineering tools (e.g. personas) using a case study

    Contents

    1. basics

    • Introduction and motivation
    • Definition of software ergonomics
    • Perception
    • Memory and experience
    • Processes of action
    • Communication

    2. implementation

    • Norms and laws
    • Guidelines
    • Hardware
    • Forms of interaction
    • Graphical dialog systems

    3. user-centered design

    • Introduction
    • Web usability
    • Accessibility
    • Tools of usability engineering

    4. further contents

    In consultation with the students, one to three of the following topics will be covered. The list will be expanded as required

  • Gesture control
  • User interfaces in computer games
  • User interfaces for mobile systems
  • Brain-computer interfaces
  • Multitouch interfaces
  • Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    • written written examination
    • Project work with oral examination
    • study achievements during the semester (bonus points)

    Requirements for the awarding of credit points

    • passed written examination
    • passed oral examination
    • successful project work

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual

    Literature

    Die im jeweiligen Semester eingesetzte Prüfungsform (z.B. mündliche Prüfung) wird zu Beginn der Veranstaltung bekanntgegeben. Dies gilt ebenfalls für eine möglicherweise genutzte Bonuspunkteregelung.

    Mobile App Engineering
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46847

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successfully completing the module, students will be able to ...

    • understand the software engineering challenges of mobile app development,
    • develop a mobile app across all development phases (from requirements analysis to conception & design to design, implementation, testing and commissioning)
    • create and present relevant mobile app-specific development and results documents,
    • the processes, activities, methods, techniques, languages and tools ...
      • to use for a mobile app-specific requirements analysis 
      • to be used for the conception and design of mobile apps,
      • to be used for the implementation of mobile apps,
      • to be used for testing mobile apps,
      • to be used for the commissioning of mobile apps,
    • to be able to apply the roles and responsibilities in the field of mobile app engineering
    • .

    Contents

    The aim and content of the course is to teach suitable methods, techniques, languages and tools to professionally conceptualize, design, develop, test and commission mobile apps from a software engineering perspective. The entire life cycle of a mobile app is considered, including:

    • User-oriented collection and specification of the functional and non-functional requirements for a mobile app
    • GUI prototyping with low- and high-fidelity prototypes
    • UX/UI design,
    • Specification of the interaction design
    • Specification and the individual screen pages,
    • Implementation of mobile apps,
    • Testing mobile apps
    • Processes and activities for the go-live of a mobile app

    The phases and activities to be carried out are described and illustrated in a practical way using suitable methods, techniques, languages and tools based on a large industrial mobile app development project.

    In the practical part of the course - from the results and presentations of which the performance assessment is also derived - selected requirements, conception, design, development and test activities are carried out in project teams of four in order to develop a mobile app independently and autonomously. The students then present the results they have developed in the practical part in a 20-minute presentation on two dates.

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Internship accompanying the lecture 
    • Processing programming tasks on the computer in individual or team work
    • Presentation of the results by the student project groups

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of two partial examinations:
    1. By the middle of the lecture period, the following result documents on the conception and design of a mobile app are created and developed in project groups of four students and presented in a 20-minute presentation by 2 students; 50 (out of a total of 100) points can be achieved:
      • UML use case diagram
      • 4 personas & 4 scenarios
      • Product backlog with all user stories
      • UML class diagram
      • UML state diagram of the click flow of the mobile app
      • Static HiFi GUI prototype
    2. In the last week of lectures, the other two students from the 4-person project group present the results of the design, implementation and testing of the mobile app with a further 50 (out of a total of 100) achievable points:
      • Specification of the individual GUI pages
      • Test plan, test protocols and results
      • Runnable mobile app 
    The overall grade is then calculated by adding up the points achieved: a "sufficient (4.0)" can be achieved from 50 points and a "very good (1.0)" from 95 points.

    Requirements for the awarding of credit points

    If at least 50 total points are achieved, a grade of 4.0 (sufficient) is awarded and the teaching module is successfully passed so that the required credit points are awarded.

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual

    Literature

    • Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.

    Moderne Datenbanken
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46892

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successful participation in the module courses and completion of the course-related  project, students are able to design, implement and evaluate database applications and distributed database architectures with NoSQL databases. Expert knowledge:

    • Know and use NoSQL database models and demonstrate possible applications
    • .
    • Know and explain materialized and virtual information integration.
    • Evaluate and explain distributed database architectures for big data applications.
    • Explain and critically evaluate exemplary applications of polyglot persistence.Evaluate big data applications taking into account ethical, social and Business Studies aspects.

    Social competence:

    • Developing, communicating and presenting non-relational database applications in small groups
    • .
    • Collaboratively create and compare non-relational database applications with relational solutions.
    • Critically evaluate solutions from others and provide constructive feedback.

    Professional field orientation:

    • Know the requirements of different job profiles in the database environment (database administrator. Database developer, application developer, data protection officer)
    • .

    Contents

    1. Distributed databases and big data applications
    2. Architectures for distributed database applications
    3. Requirements and selection of databases (CAP theorem)
    4. NoSQL databases, multi-model and NewSQL databases
    5. Polyglot persistence
    6. Selected algorithms (e.g. map-reduce algorithm)
    7. Current applications

     

    Teaching methods

    • Seminar-style teaching with flipchart, smartboard or projection
    • Processing programming tasks on the computer in individual or team work
    • Project work accompanying the lecture with final presentation
    • Group work
    • Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
    • Homework to accompany the course
    • The lecture is offered as a video
    • Inverted teaching (inverted classroom)
    • Concluding presentation

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a written exam (60 minutes) and coursework during the semester.
    In the written exam, students should demonstrate basic knowledge of theoretical concepts, database architectures, database models  and justify the selection of databases for given application scenarios.
    Through coursework during the semester, students should design a self-selected application scenario in small groups and evaluate, present and reflect on the implementation with various NoSQL databases.

    Requirements for the awarding of credit points

    The performances are graded and must be passed with a total grade of 4.0. The performances consist of:
    • passed written examination (60%-100%) and
    • successful presentation (0%-40%) or successful mini-project (project-related work) (0%-40%)

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science

    Literature

    • S. Edlich, A. Friedland, J. Hampe, B. Brauer, NoSQL Einstieg in die Welt nichtrelationaler Web 2.0 Datenbanken, Hanser Verlag 2010
    • M. Kleppmann, Designing data-intensive applications, O'Reilly Media (2017)
    • A. Bifet, Machine learning for data stream, MIT-Press (2017)
    • B. Ellis, Real-time analytics, Wiley & Sons (2014)
    • Aktuelle Fachliteratur

    Numerische Algorithmen
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46840

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successful participation in the module courses and completion of the project work, students are able to ...

    • calculate numerical representations
    • analyze numerical errors
    • calculate fixed points, zeros and roots numerically
    • calculate derivatives and integrals numerically
    • Solve linear systems of equations numerically
    • numerically solve eigenvalue and eigenvector problems
    • calculate approximating and interpolating polynomials and splines numerically

    Contents

    - Numerical representations and error analysis
    - LR decomposition
    - QR decomposition (Givens and Householder)
    - Cholesky decomposition
    - Banach's fixed point theorem
    - Newton method
    - Heron method
    - Secant method
    - Descent method
    - Divided-difference method
    - Trapezoidal and Simpson's rule
    - Standards and sequences in multidimensional
    - Total step, single step and SOR methods
    - Von Mises-Geiringer method
    - Polynomial interpolation and approximation
    - Spline interpolation and approximation
    - Bilinear interpolation
    - Transfinite interpolation function

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor of Medical Informatics

    Literature

     
    • B. Lenze, Basiswissen Angewandte Mathematik - Numerik, Grafik, Kryptik. Eine Einführung mit Aufgaben, Lösungen, Selbsttests und interaktivem Online-Tool. Springer Vieweg Wiesbaden, 2020, zweite Auflage
    • G, Bärwolf, Numerik für Ingenieure, Physiker und Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2017, dritte Auflage
    • G. Farin, Curves and Surfaces for CAGD, Academic Press, San Diego, 2002, fünfte Auflage.
    • M. Hermann, Numerische Mathematik, de Gruyter-Oldenbourg, 2011, dritte Auflage
    • T. Huckle, S. Schneider, Numerik für Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2006, zweite Auflage.
    • H. Prautzsch, W. Boehm, M. Paluszny, Bezier and B-Spline Techniques, Springer-Verlag, Berlin-Heidelberg-New York, 2010, erster Nachdruck.
    • R. Schaback, H. Wendland, Numerische Mathematik, Springer-Verlag, Berlin-Heidelberg-New York, 2005, fünfte Auflage.
    • J. Werner, Numerische Mathematik 1 und 2, Vieweg, Wiesbaden, 1992
     

    Programmierkurs 2
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      43022

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successfully completing the module, students will be able to:

    Knowledge and understanding:

    • name the problem domains of the languages under consideration
    • .
    • describe the memory management of the languages under consideration
    • .
    • describe different approaches to exception handling.
    • explain the differences between procedural and object-oriented programming.explain the difference between dynamic and static binding.understand the specifics of multiple inheritance.describe different approaches for the realization of properties.


      Use, application and generation of knowledge:

      • implement basic dynamic structures
      • .
      • use abstract classes, interfaces and polymorphism in the languages under consideration.
      • assess the impact of platform dependencies.
      • use pointers and references in a targeted manner.
      • Use data types as parameters.
      • Use operator overloading.


      Communication and cooperation:

      • present your own programs in the internship
      • to discuss programs in the forum (live programming)


      Scientific self-image / professionalism:

      • to analyze already known concepts in more detail
      • .
      • select an appropriate language for a given problem domain.
      • transfer solutions between different languages.

    Contents

    Module description:
    Deepening programming knowledge through a comparative analysis of the Java, C, C++ and C languages; . Identification of individual strengths and weaknesses of the individual languages depending on specific tasks.

    Module structure:
    • Introduction to the programming languages C, C++ and C;
    • Comparison of procedural and object-oriented programming concepts
    • Program structuring
    • Variables, pointers and references
    • Compound data types
    • Dynamic memory management
    • Type conversion
    • Constructors and destructors
    • Overloading of operators
    • Exception handling
    • Virtual element functions
    • Abstract classes and interfaces
    • Polymorphism
    • Multiple inheritance
    • Generic programming and templates

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing, projection and live programming
    • Solving practical exercises in individual or team work
    • Processing programming tasks in the practical course (on the computer in individual or team work)

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Written written examination (60 - 90 minutes)

    .

    Requirements for the awarding of credit points

    Passed written exam

    .

    Applicability of the module (in other degree programs)

     
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • Kernighan B.W., Ritchie D.M.; "The C Programming Language", Prentice Hall, 1988
    • Breymann U.; "C++ programmieren", Carl Hanser Verlag, München, 2023
    • Stroustrup, B.; "The C++ Programming Language", Addison-Wesley, Boston, 2013
    • Stellman, A., Green, J.; "Head First C; ", O'Reilly, Beijng, 2012
    • Troelsen, A., Japikse, P.; "Pro C# 10.0 with .NET 6", APRESS, New York, 2022

    Prozessmanagement und Organisationsentwicklung im Gesundheitswesen
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46888

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    Knowledge:

    • Objectives of process-oriented corporate management
    • Process management at a glance
    • Techniques of process optimization
    • Methods of activity-based costing
    • Organizational development goals
    • Evolutionary and revolutionary organizational concepts

    Capabilities:

    • Create a process map
    • Identify and analyze processes
    • Optimize processes
    • Improve processes with IT support
    • Calculate process costs
    • Describe functional and divisional forms of organization
    • Apply tools of change management

    Contents

    Process management:
    • Process management at a glance
    • Integrated management concepts
    • From functional organization to process organization
    • Business process management and process thinking
    • Classification of processes
    • Elements and subsequent relationships
    • Structuring the process flows
    • Process optimization: from actual to target concept
    • Implementation of the target concept

    Organizational development:

    • Change as an ongoing task
    • Organizational design
    • Organizational development
    • Corporate culture and organizational learning
    • Evolutionary and revolutionary concepts

    Teaching methods

    • Lecture in seminar style, with blackboard writing and projection
    • Solving practical exercises in individual or team work
    • Planning game

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual

    Literature

    • Kretzmann, Willi (2009): Geschäftsprozessmanagement im Medizinischen Versorgungszentrum Konzept, Entwicklung und Realisierung. In: Hellmann W (Hrsg.) Handbuch Integrierte Versorgung, medhochzwei Verlag (online)
    • Kretzmann, Willi (2010): Wie Change Management im MVZ zum strategischen Vorteil wird. In: Hellmann Willi (Hrsg.) Handbuch Integrierte Versorgung, medhochzwei Verlag (online)
    • Kretzmann, Willi (2010): Unternehmensführung im Kontext eines integrierten Managementsystems. In: Hellmann, W., Kretzmann, W., Kurscheid, C.,Eble, S. (Hrsg.) Medizinische Versorgungszentren erfolgreich führen und weiterentwickeln, MWV 2010
    • Schmelzer, Hermann J., Sesselmann, Wolfgang (2010): Prozessmanagement in der Praxis, Hanser 2010

    Robotik
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46855

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological competence:

    After completing the lecture, students will be able to

    • Understand and apply methods and concepts of robotics
    • design and implement stationary and mobile robotics applications
    • set up kinematic equations for mobile and stationary robots
    • select components for robotics applications
    • configure and program mobile and stationary robots

    Contents

    • Objectives and areas of application of robotics
    • Design of stationary and mobile robots
    • Kinematics of stationary robots
    • Applications of stationary robots
    • Subsystems of robots (joints, drives, actuators and sensors)
    • Kinematics of mobile wheel-driven robots
    • Self-localization and navigation of mobile robots

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Exercise accompanying the lecture
    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor of Computer Science

    Literature

    • Corke, Peter: Robotics, Vision and Control: Fundamental Algorithms in MATLAB, second edition, Springer, 2017
    • Weber, Wolfgang: Industrieroboter: Methoden der Steuerung und Regelung, Carl Hanser Verlag, 3. Auflage, 2017
    • Siegwart, Roland; Nourbakhsh, Illah R.: Introduction to Autonomous Mobile Robots, MIT Press, 2nd Edition, 2011
    • Hesse, Stefan; Malisa, Viktorio (Hrsg.): Taschenbuch Robotik ­ - Montage ­ - Handhabung, Carl Hanser Verlag, 2010
    • Hertzberg, Joachim; Lingemann, Kai; Nüchter, Andreas: Mobile Roboter - Eine Einführung aus Sicht der Informatik, Springer Vieweg Verlag, 2012

    Seminar (Methodik)
    • WP
    • 2 SWS
    • 2.5 ECTS

    • Number

      451811

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30 h

    • Self-study

      45 h


    Learning outcomes/competences

    After successfully completing this module, students will be able to


    Know and understand

    • Name and understand the competencies corresponding to the methodological focus of the seminar.

    Use, apply and generate knowledge

    • . Apply the methodological skills corresponding to the focus of the seminar in studies and work.
    • Apply the methods learned in the course to an interdisciplinary topic.
    • Independently research and evaluate technical and scientific content.
    • Independently develop technical-scientific texts.
    • Create presentations

    Communication and cooperation

    • Present an interdisciplinary topic to fellow students in an understandable way.
    • Present results.
    • Work in groups and interact within the groups.
    • Present and defend content in groups.

    Scientific self-image / professionalism

    • Structure scientific texts independently.

    Contents

    The seminars include topics that expand students' interdisciplinary scientific and methodological skills. The topics are offered each semester with new, up-to-date content by all professors and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Presentation techniques, introduction to scientific work, planning and conducting data surveys.

    Alternatively, a methodologically oriented course can be taken in the "Studium Generale" in the scope of 2 SWS. The list of selectable courses can be found in the university's electronic information service (https://fh.do/inf/generale).

    Teaching methods

    Seminar

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    Presentation

    Requirements for the awarding of credit points

    Regular participation in at least 2/3 of the attendance dates

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics

    Literature

    Literatur muss vom Studierenden selbst ermittelt werden.

    Übergreifend:

    • Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011

    Softwaretechnik C (Softwaremanagement)
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      45261

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Knowledge and understanding:
    After successful participation in the module courses, students will be able to

    • Presenting the goals, methods and relevance of software management
    • Determine suitable procedure and process models in the context of a software project
    • Describe the required methodology as well as the distribution of tasks and roles of the communicated procedure and process models
    • Name the methods, processes and activities of product management for software
    • Determine methods, processes and activities of process improvement as well as appropriate process improvement frameworks with respect to a business context 

    Use, application and generation of knowledge:
    After successfully completing the module courses, students will be able to
    • classify software projects with regard to their framework conditions and requirements and assess their complexity
    • apply methods for eliciting (software) requirements
    • Organize the documentation and management of (software) requirements, especially in the context of agile procedure and process models
    • Organize risk management methods, processes and activities in software projects
    • Organize methods, processes and activities for planning and controlling software projects
    • Organize methods, processes and activities of quality management in software projects
    • Name methods, processes and activities of configuration management in software projects and organize methods, processes and activities of release management in software projects

    Communication and cooperation:
    After successfully completing the module courses, students will be able to
    • to independently structure core elements of software management and activities for coordination and communication in the creation of work results in small groups

    Scientific self-image / professionalism:
    After successful participation in the module courses, students will be able to
    Classify software projects with regard to their framework conditions and requirements and structure them using software management methods

    Contents

    • Introduction to software management: General overview of relevance as well as concepts and methods of software management
    • Procedure and process models in software engineering: Classification and methodology of relevant procedure and process models in software engineering, including the waterfall model, V-Model XT, Kanban, Scrum and SAFe, as well as the values and principles of the Agile Manifesto
    • Requirements management: classification and methodology of common processes, activities and concepts of requirements management, including elicitation techniques, administration and documentation in an agile context
    • Risk management: Classification and methodology of common processes, activities and concepts of risk management in a classic and agile context
    • Project management: Classification and methodology of processes, activities and concepts in the areas of planning and control of project management in a classic and agile context
    • Quality management: Classification and methodology of common processes, activities and concepts of quality management in a classic and agile context
    • Configuration management: Classification and methodology of common processes, activities and concepts of configuration management
    • Product Management: Classification and Methodology of Common Processes, Activities and Concepts of Product Management
    • Release management: Classification and methodology of common processes, activities and concepts of release management in a classic and agile context
    • Process improvement: Classification and methodology of common processes, activities and goals of process improvement, especially for maturity-based and agile approaches
    • Common framework models of process improvement 

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Internship accompanying the lecture with group work and practical exercises 
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a written exam in which students explain the methods and concepts of software management taught and use their knowledge to analyze practical case studies.
    In the context of semester-long coursework (bonus points) with a final presentation, students apply their knowledge to a case study.

    Duration: 60-90 min

    Requirements for the awarding of credit points

    The performances are graded and must be completed with a minimum grade of sufficient (4.0).

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual

    Literature

    • Balzert, H. (2008): Lehrbuch der Softwaretechnik: Softwaremanagement, 2. Auflage, Heidelberg: Spektrum Akademischer Verlag.
    • Balzert, H. (2009): Basiskonzepte und Requirements Engineering, 3. Auflage, Heidelberg: Spektrum Akademischer Verlag.
    • Richard Kastner, Dean Leffingwell: Safe 5.0 Distilled: Achieving Business Agility With the Scaled Agile Framework. Addison Wesley, 2020.
    • Ludewig, J., Lichter, H. (2013): Software Engineering Grundlagen, Menschen, Prozesse, Techniken, 3. korrigierte Auflage, Heidelberg: dpunkt-Verlag.
    • Pichler, R. (2009): Scrum - Agiles Projektmanagement erfolgreich einsetzen, Heidelberg: dpunkt-Verlag.
    • Pohl, K.; Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
    • Röpstorff, S., Wiechmann, R. (2016): Scrum in der Praxis, 2. aktualisierte Auflage. Heidelberg: dpunkt.verlag.
    • Sommerville, I. (2018): Software Engineering, 10. aktualisierte Auflage, München: Pearson.
    • Spitzcok, N.; Vollmer, G., Weber-Schäfer, U. (2014): Pragmatisches IT-Projektmanagement, 2. aktualisierte und überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
    • Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.
    • Vollmer, G. (WS 2019/2020): Unterlagen zur Lehrveranstaltung "Softwaretechnik C - Softwaremanagement".
    • Winkelhofer, G. (2005): Management- und Projekt-Methoden, 3. Auflage, Berlin, Heidelberg: Springer.

    Softwaretechnik D (Qualitätssicherung und Wartung)
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46264

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Teaching the knowledge required to achieve a defined level of quality in software development. The analytical and constructive measures for quality assurance are known and can be applied in a targeted manner. Methodical approach to software maintenance.

    Technical and methodological competence:

    • Differentiating between analytical and constructive measures for quality assurance
    • Naming typical sources of error
    • Selecting suitable tools in the context of constructive software engineering
    • Selecting suitable metrics for quality measurement
    • Knowing different integration strategies
    • Recognizing the influence of automation on quality
    • Systematically derive test cases
    • Performing manual test procedures
    • Applying analytical test procedures
    • Naming risks, problems and principles of maintenance
    • Organizing software maintenance


    Interdisciplinary methodological competence:

    • Operationalizing the concept of quality via quality models
    • Understanding that testing is a necessary but not sufficient measure to ensure quality
    • Conducting target group-oriented presentations


    Professional field orientation:

    • Creating a quality manual
    • Selecting and using suitable tools (constructive software engineering)

    Contents

    • Quality models
    • Sources of error
    • Constructive measures
    • Manual test methods
    • Tools
    • Black box test
    • White box test
    • Metrics
    • Static code analysis
    • Test management
    • Automation (software infrastructure)
    • Load test
    • Maintenance and care

    Teaching methods

    • Lecture in interaction with the students, with blackboard writing and projection
    • Solving practical exercises in individual or team work

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    written exam paper

    Requirements for the awarding of credit points

    passed written exam

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Computer Science Dual
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science

    Literature

    • Balzert, H.; "Lehrbuch der Softwaretechnik, Softwaremanagement", Spektrum Akademischer Verlag, Heidelberg, 2008
    • Binder, R.V.; "Testing Object-Oriented Systems", Addison-Wesley, Boston, 2000
    • Hoffmann, D.W.; "Software-Qualität", Springer Vieweg, Berlin, 2013
    • Liggesmeyer, P.; "Software-Qualität", Spektrum Akademischer Verlag, Heidelberg, 2009
    • Ludewig, J.; Lichter, H.; "Software Engineering", dpunkt.verlag, Heidelberg, 2010
    • Spillner, A.; Linz, T.; "Basiswissen Softwaretest", dpunkt.verlag, Heidelberg, 2012
    • Sneed, H.M.; Seidl, R.; Baumgartner, M.; "Software in Zahlen", Hanser, München, 2010

    Studium Generale
    • WP
    • 2 SWS
    • 2.5 ECTS

    • Number

      451815

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      30h

    • Self-study

      45 h


    Learning outcomes/competences

    In this module, students can choose from a selection of cross-university courses. The competencies are defined by the respective course.

    Contents

    In this module, you can choose from a selection of cross-university courses. The content is defined by the respective course.

    Teaching methods

    In this module, students can choose from a selection of cross-university courses. The forms of teaching are defined by the respective course.

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    In this module, students can choose from a selection of cross-university courses. The forms of examination are defined by the respective course.

    Requirements for the awarding of credit points

    In this module, you can choose from a selection of cross-university courses. The prerequisites are defined by the respective course.

    Applicability of the module (in other degree programs)

    • Bachelor's degree in Business Informatics
    • Bachelor of Computer Science
    • Bachelor of Medical Informatics

    Literature

    Literatur muss vom Studierenden selbst ermittelt werden.

    Übergreifend:

    • Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011

    Virtualisierung und Cloud Computing
    • WP
    • 4 SWS
    • 5 ECTS

    • Number

      46810

    • Language(s)

      de

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    Technical and methodological skills:

    •  Model object-oriented extensions using EER models and implement them in relational databases.
    • Discuss the limitations of the relational database model using examples.
    • Implement complex user views and stored procedures for exemplary application scenarios.
    • Design and implement database applications in Java.
    • Explain the 5-level model of a database management system.
    • Explain concepts of storage and access management.
    • Use examples to apply the methods of access optimization and transaction management.
    • Evaluate performance optimization options and apply SQL tuning methods.

      Social skills:

      • Developing, creating, communicating and presenting database applications in small groups

       

    Contents

    Database implementation

    • Storage management
    • Logical and physical access optimization
    • Transaction management
    • Distributed databases
    • Performance optimization and SQL tuning

    Development of database applications

    • Data modeling (EER model and logical design of object-oriented concepts)
    • Limitations of the relational model
    • Object-relational mapping frameworks
    • Ensuring data integrity and data protection (view hierarchies, stored procedures, triggers)
    • Conception, design and implementation of database applications in JAVA

    Teaching methods

    • Solving practical exercises in individual or team work
    • Internship accompanying the lecture
    • Processing programming tasks on the computer in individual or team work
    • Active, self-directed learning through Internet-supported tasks, sample solutions and accompanying materials
    • Exercises or projects based on practical examples
    • The lecture is offered as a video
    • Inverted teaching (inverted classroom)

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    The module examination consists of a written exam (60-90 minutes) and coursework during the semester.
    In the written exam, students should demonstrate basic knowledge of theoretical concepts, database architecture, performance optimization and development of database applications and demonstrate their skills in solving small application problems.

    Through semester-long examinations (project-related work), students should design, develop, implement and present a database application for a self-chosen application scenario.

    Requirements for the awarding of credit points

    The performances are graded and must be passed with a total grade of 4.0. The performances consist of:
    • passed written examination (80%)
    • successful mini-project (project-related work)  (20%)

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor's degree in Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual

    Literature

    • R. Elmasri, S. Navathe, Grundlagen von Datenbanksystemen, 2009
    • A. Kemper, A. Eickler, Datenbanksysteme (Eine Einführung), 2015
    • G. Saake, K.-U. Sattler, A. Heuer, Datenbanken Implementierungstechniken, 2011
    • R. Niemiec, Oracle database 12c release 2 performance tuning tips & techniques, 2017
    • R. Panther, SQL-Anfragen optimieren, 2014

    6. Semester of study

    Bachelorarbeit
    • PF
    • 4 SWS
    • 15 ECTS

    • Number

      103

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h


    Learning outcomes/competences

    After successfully completing this module, students will be able to:

    Know and understand

    - Define, differentiate and explain key terms and concepts of information security (including IT security, information security, protection goals, vulnerability, threat, attack, risk, security measure).
    - explain the human factor and security awareness for information security.
    - describe the main features of the legal and regulatory framework (including GDPR).
    - explain the basics of applied cryptography, access control and authentication (including AES, hash functions, MAC, RSA/ECC, DAC, MAC, RBAC, password procedures, MFA).
    - explain essential standards and best practices (including ISO/IEC 27000 series, IT-Grundschutz, OWASP) with regard to objectives and structure.

    - use, apply and generate knowledge

    - research and evaluate information on vulnerabilities and threats and incorporate it into security-relevant decisions.
    - Apply norms, standards and best practices (e.g. ISO/IEC-27000, IT-Grundschutz, OWASP) to specific application scenarios.
    - Identify assets for given systems, model threats and derive security requirements from them.
    - select suitable cryptographic, access and authentication mechanisms (e.g. AES, SHA-2/-3, RSA/ECC, Argon2, MFA, NIST 800-63B) and apply them as examples.
    - apply basic procedures of penetration testing and OWASP projects (e.g. Top 10, ASVS, Testing Guide) as examples.

    Communication and cooperation

    - Prepare risks, threats and security measures in a manner appropriate to the target group and communicate them to technical and non-technical stakeholders.
    - Discuss the results of asset surveys as well as system and threat modeling in a team and jointly develop security concepts.
    - coordinate security-conscious procedures in development and operational processes in a team.

    Scientific self-image / professionalism

    - justify security-relevant decisions taking into account legal, ethical and social aspects.
    - classify their own responsibility in dealing with sensitive data and observe professional ethical principles.
    - independently track relevant developments, standards and best practices and integrate them into their own professional actions.

    Contents

    Terminology
    - IT security, information security, difference between security and safety
    - System, fact, assumption, asset
    - Protection objective (CIA and authentication)
    - Weak point, vulnerability, threat, attack, attacker types
    - Risk
    - Security objective, security requirement
    - Security measure
    Human factor, Security awareness
    Legal framework, European General Data Protection Regulation
    Standards and best practices
    - ISO/IEC 27000 series
    - IT baseline protection
    - OWASP
    Applied cryptography
    - Symmetric encryption (basics, AES, block modes, padding, pitfalls)
    - Hash functions (types of attack, SHA-2 family, SHA-3 family), MAC
    - Asymmetric cryptography (basics, DH, RSA, ECC, padding, pitfalls, digital signatures, certificates)
    Access control
    - Basics (DAC, MAC, RBAC, Deny by Default, Least Privilege)
    - Advanced models (ABAC, ReBAC), modeling
    Authentication
    - Basics of authentication (Types, MFA, entropy)
    - Password-based authentication (Linux password databases, types of attack, Salt, Argon2, NIST 800-63B)
    - Basics of software development and information security
    - Asset identification and analysis
    - Threat modeling
    - Best practices (OWASP Top 10, SAMM, ASVS, Testing Guide)
    - Penetration testing

    Teaching methods

    - Lecture in interaction with the students, with blackboard writing and projection
    - Solving practical exercises in individual or team work
    - Practicals

    Participation requirements

    See the respective valid examination regulations (BPO/MPO) of the study program.

    Forms of examination

    - Written exam (80%)
    - Internships (20%)

    Requirements for the awarding of credit points

    - Passed written exam
    - Passed internships

    Applicability of the module (in other degree programs)

    • Bachelor of Business Informatics
    • Bachelor of Software and Systems Engineering (dual)
    • Bachelor of Computer Science
    • Bachelor of Computer Science
    • Bachelor's degree in Medical Informatics
    • Bachelor of Medical Informatics Dual
    • Bachelor of Computer Science Dual
    • Bachelor of Computer Science Dual

    Literature

    - R. Anderson: Security Engineering: A Guide to Building Dependable Distributed Systems, 3. Auflage, John Wiley & Sons Inc., 2020
    - C. Eckert: IT Sicherheit (Konzepte, Verfahren, Protokolle), 11. Auflage, De Gruyter Oldenbourg, 2023
    - ISO/IEC 27000: Information technology – Security techniques – Information security management systems – Overview and vocabulary, 2018
    - K. Schmeh: Kryptografie – Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016

    Notes and references

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