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Bachelor Informationstechnik mit PR / Auslandsstudiensemester

Fast facts

  • Department

    Informationstechnik

  • Stand/version

    2023

  • Standard period of study (semester)

    7

  • ECTS

    210

Study plan

1. Semester2. Semester3. Semester4. Semester5. Semester6. Semester

Grundlagen der Informationstechnik

  • PF
  • 4SWS
  • 5ECTS

Grundlagen der Elektrotechnik

  • PF
  • 4SWS
  • 5ECTS

Grundlagen der Signal- und Systemtheorie

  • PF
  • 4SWS
  • 5ECTS

Connected Car und V2X

  • PF
  • 4SWS
  • 5ECTS

Fachpraktikum 2 Informationstechnik

  • PF
  • 5SWS
  • 5ECTS

Bachelor Arbeit und Abschluss-Kolloquium

  • PF
  • 4SWS
  • 15ECTS

Mathematik 1

  • PF
  • 4SWS
  • 5ECTS

Informatik 2

  • PF
  • 4SWS
  • 5ECTS

Informatik 3

  • PF
  • 4SWS
  • 5ECTS

Automotive Systems Engineering

  • PF
  • 4SWS
  • 5ECTS

Projektorientiertes Arbeiten 1

  • PF
  • 4SWS
  • 4ECTS

Praxis-/Auslandssemester

  • PF
  • 4SWS
  • 30ECTS

Informatik 1

  • PF
  • 4SWS
  • 5ECTS

Kommunikationstechnik

  • PF
  • 4SWS
  • 5ECTS

Kommunikationsnetze und IT-Sicherheit

  • PF
  • 4SWS
  • 5ECTS

Autonome Systeme

  • PF
  • 4SWS
  • 5ECTS

Seminar Informationstechnik

  • PF
  • 4SWS
  • 5ECTS

Projektorientiertes Arbeiten 2

  • PF
  • 2SWS
  • 15ECTS

Mikroprozessortechnik

  • PF
  • 4SWS
  • 5ECTS

Mathematik 2

  • PF
  • 4SWS
  • 5ECTS

Messtechnik und Fehlerrechnung

  • PF
  • 4SWS
  • 5ECTS

Fachpraktikum 1 Informationstechnik

  • PF
  • 5SWS
  • 5ECTS

Web Protokolle und Services

  • PF
  • 4SWS
  • 10ECTS

Physik 1

  • PF
  • 4SWS
  • 5ECTS

Physik 2

  • PF
  • 4SWS
  • 5ECTS

Mobile Robotik

  • PF
  • 4SWS
  • 5ECTS

Informatik 4

  • PF
  • 4SWS
  • 5ECTS

Praxisnahe Grundlagen 1

  • PF
  • 5SWS
  • 5ECTS

Praxisnahe Grundlagen 2

  • PF
  • 5SWS
  • 5ECTS

Modellbildung & Simulation für die Digitalen Technologien

  • PF
  • 4SWS
  • 5ECTS

Schlüsselqualifikationen

  • PF
  • 4SWS
  • 4ECTS

Modellbildung & Simulation für die Informationstechnik

  • PF
  • 4SWS
  • 5ECTS

Sensorik und Simulation

  • PF
  • 4SWS
  • 5ECTS

Praxisnahe Grundlagen 3

  • PF
  • 5SWS
  • 5ECTS

Signalverarbeitung & Regelungstechnik

  • PF
  • 4SWS
  • 5ECTS

Robotik

  • PF
  • 4SWS
  • 5ECTS

Softwaretechnik

  • PF
  • 4SWS
  • 5ECTS

Smart Mobility

  • PF
  • 4SWS
  • 5ECTS

Compulsory elective modules (43)

Übertragungstechnik

  • PF
  • 4SWS
  • 5ECTS

    • Compulsory elective modules 1. Semester

    • Compulsory elective modules 2. Semester

    • Compulsory elective modules 3. Semester

    • Compulsory elective modules 5. Semester

    • Compulsory elective modules 6. Semester

Module overview

1. Semester of study

Grundlagen der Informationstechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10020

  • 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 exam (between 60 and 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

Mathematik 1
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10010

  • 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:

  • explain the influence of the Object class
    • .
  • describe the basic structure of the Collection API.
  • explain exception handling.
  • explain the basics of serialization.
    • explain the relationship between processes and threads.Name the characteristics of declarative programming.


Use, application and generation of knowledge:

  • Find and use information in API documentation
    • .
  • decouple components via interfaces
    • .
  • to structure an application program in abstraction layers.
    • manage technical objects in generic collections.
  • implement different sort orders
    • .
  • use prefabricated components in a targeted manner via an application programming interface (API).
    • read and write access to the file system with a program.to use data streams.
  • implement concurrent calculations
    • .
  • implement a graphical user interface (GUI) from a technical point of view.
  • to realize declarative solutions.


Communication and cooperation:

  • to enable teamwork through abstraction and the separation of responsibilities
  • present your own programs in the internship
    • .


Scientific self-image / professionalism:

  • Structuring application programs
    • .
  • to use prefabricated components in a targeted manner
    • .
  • to better estimate the effort of programming activities.

Contents

Module description:
Teaching 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.

Module structure:
  • In-depth study of object-oriented programming in Java (packages, object class, abstract classes, interfaces, polymorphism)
  • Exception handling
  • Use of generic collections for object management
  • Determining the sort order for objects
  • Access to the file system and organization of files (Java IO)
  • 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, projection and live programming
  • Solving practical exercises in individual or team work
  • Processing a programming project 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 exam (between 60 and 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

Literature

  • Horstmann, C.; "Core Java, Volume 1: Fundamentals", Pearson, Hoboken, New Jersey, 2024
  • Horstmann, C.; "Core Java, Volume 2: Advanced Features", Pearson, Hoboken, New Jersey, 2024
  • Horstmann, C.; "Core Java for the Impatient", Addison-Wesley, Hoboken, New Jersey, 2025
  • Urma, R.-G., Fusco, M., Mycroft, A.; "Modern Java in Action: Lambdas, streams, functional and reactive programming", Manning, Shelter Island, 2019
  • Epple, A.; "JavaFX 8: Grundlagen und fortgeschrittene Techniken", dpunkt.verlag, Heidelberg, 2015
  • Sharan, K., Späth, P.; "Learn JavaFX 17: Building User Experience and Interfaces with Java", Apress, New York, 2022

Informatik 1
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10160

  • Duration (semester)

    1

  • Self-study

    150 h

Learning outcomes/competences

Through the project work, students learn the following skills, which prepare them to write their final thesis later on and qualify them for their career entry:

  • 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 work using scientific working methods (including literature research, correct citation) 
  • Evaluate the results of your own work
    • .
  • Ability to work in a team with developers and (where possible) users, in particular: 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 content of a project work is assessed according to effort and complexity, originality and independence, scientific working technique and methodical approach, practical implementation, style and external form.

Students have the right to suggest a project topic. The project should preferably be carried out outside the university (further details are regulated by the VA-PAAA-EXT procedural instructions). Group work is desired. The specific knowledge directly required in the projects will be taught in block courses if necessary. Regular project meetings give students the opportunity to acquire the above-mentioned teamwork skills by practicing them. In particular, quality assurance is trained through the presentation of results from analysis, design and implementation.

In general, project work 1 and 2 are completed as one project; in individual cases, they can be separated (see curriculum).

The total workload for project work 1 and 2 is 450 hours.

Teaching methods

  • Project work; final presentation

Participation requirements

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

Forms of examination

Project work with oral examination

Requirements for the awarding of credit points

Successful project 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'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

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

Mikroprozessortechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10040

  • 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

Physik 1
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10103

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h

Learning outcomes/competences

After successfully completing the module, students will have mastered important methods and algorithms of modern data analysis for recognizing patterns and structures in large data sets. In particular, they will be 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.

Contents

The module teaches the phases of data mining as described in the KDD and CRISP model. Data, relations, data preprocessing and outlier detection are covered. Methods of data analysis include cluster analysis (k-Means, hierarchical agglomerative methods), classification methods (nearest neighbor, naive Bayes, linear discriminant analysis, decision trees, support vector machines, logistic regression) and association analysis.  

Teaching methods

Lecture in interaction with the students, with blackboard writing and projection, solving practical exercises in individual or team work, working on programming tasks on the computer in individual or team work, exercises or projects based on practical examples
n examples

Participation requirements

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

Forms of examination

  • Project work with oral examination

Requirements for the awarding of credit points

  • passed oral examination
  • successful project 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

Praxisnahe Grundlagen 1
  • PF
  • 5 SWS
  • 5 ECTS

  • Number

    10050

  • 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:

  • Distinguishing between IT management and IT service management
  • Naming the reasons for and objectives of using ITIL
  • Differentiating the different phases of the ITIL lifecycle
  • Use case studies to deepen the knowledge gained and develop your own solutions in the ITIL environment
  • Design and implement your own ITIL implementation scenarios in exemplary case studies
  • Develop detailed processes based on the ITIL phases for specific practical tasks

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)
  • Evaluating classic conflicts between design and operational functions
  • Classification of DevOps and agile development in ITIL phases
  • Systematic use of IT KPIs to measure the achievement of objectives

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.)
  • Applying 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
  • Business Process Modeling Notation 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

Teaching methods

  • Lecture in seminar style, with blackboard writing and projection
  • Solving practical exercises in individual or team work
  • Case studies
  • Role-playing games
  • Exercises or projects based on practical examples

Participation requirements

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

Forms of examination

Examinations during the semester (scope 1/3) + oral examination (scope 2/3)

Requirements for the awarding of credit points

Semester examinations and oral examinations must be passed in total.

Applicability of the module (in other degree programs)

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

Literature

  • Axelos, ITIL® Service Continual Service Improvement; Edition2011; London TSO; 2013
  • Axelos, ITIL® Service Design, Edition 2011; London TSO; 2013
  • Axelos, ITIL® Service Operation; Edition 2011; London TSO; 2013
  • Axelos, ITIL® Service Strategy; Edition 2011; London TSO; 2013
  • Axelos, ITIL® Service Transition; Edition 2011; London TSO; 2013
  • 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.

2. Semester of study

Grundlagen der Elektrotechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10090

  • Duration (semester)

    1

Informatik 2
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10161

  • Duration (semester)

    1

Kommunikationstechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10081

  • Duration (semester)

    1

Mathematik 2
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10060

  • 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

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

Physik 2
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10104

  • Duration (semester)

    1

Praxisnahe Grundlagen 2
  • PF
  • 5 SWS
  • 5 ECTS

  • Number

    10110

  • Duration (semester)

    1

3. Semester of study

Grundlagen der Signal- und Systemtheorie
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10130

  • Duration (semester)

    1

Informatik 3
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10162

  • Duration (semester)

    1

Kommunikationsnetze und IT-Sicherheit
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10151

  • Duration (semester)

    1

Messtechnik und Fehlerrechnung
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10182

  • Duration (semester)

    1

Mobile Robotik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10323

  • Duration (semester)

    1

Modellbildung & Simulation für die Digitalen Technologien
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10191

  • Duration (semester)

    1

Modellbildung & Simulation für die Informationstechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10192

  • Duration (semester)

    1

Praxisnahe Grundlagen 3
  • PF
  • 5 SWS
  • 5 ECTS

  • Number

    10200

  • Duration (semester)

    1

Robotik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10153

  • Duration (semester)

    1

Smart Mobility
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10152

  • Duration (semester)

    1

Übertragungstechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10181

  • Duration (semester)

    1

4. Semester of study

Connected Car und V2X
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10242

  • Duration (semester)

    1

Automotive Systems Engineering
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10252

  • Duration (semester)

    1

Autonome Systeme
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10241

  • Duration (semester)

    1

Fachpraktikum 1 Informationstechnik
  • PF
  • 5 SWS
  • 5 ECTS

  • Number

    10281

  • Duration (semester)

    1

Informatik 4
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10163

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h

Learning outcomes/competences

Technical and methodological competence:

Knowledge:

  • Fundamental concepts of operating systems
  • Functionality of linkers and loaders
  • Principles for debugging user programs
  • Concepts of the Java VM and dynamic memory management

Application:

  • Concurrent programming under Java
  • Using the methods of the Java Runtime, Thread and ClassLoader classes
  • Using synchronous and asynchronous communication

Contents

  • Selected topics from the field of operating systems (linkers and loaders, runtime environment, memory management, mutual exclusion, deadlocks, concurrent programming, scanners, parsers)
  • Selected topics from the field of distributed systems (synchronous and asynchronous communication, clock synchronization)
    • Selected topics from the field of hardware-related programming (data types and basic operations, interrupts)

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

Literature

  • A. Silberschatz, P. Galvin: Operating System Concepts, John Whiley & Sons, 2008 (8th Edition)
  • Andrew S. Tanenbaum: Computernetzwerke, Pearson Studium, München 2003
  • Andrew S. Tanenbaum: Moderne Betriebssysteme, Pearson Studium, München 2009

Schlüsselqualifikationen
  • PF
  • 4 SWS
  • 4 ECTS

  • Number

    10270

  • Duration (semester)

    1

Sensorik und Simulation
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10253

  • Duration (semester)

    1

Signalverarbeitung & Regelungstechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10220

  • Duration (semester)

    1

Softwaretechnik
  • PF
  • 4 SWS
  • 5 ECTS

  • Number

    10251

  • Duration (semester)

    1

Einführung in Maschinelles Lernen und Künstliche Intelligenz
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10407

  • Duration (semester)

    1

Angewandte Biosignalverarbeitung - Einf. In maschinelle Lernverfahren
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10416

  • Duration (semester)

    1

Angewandte Biosignalverarbeitung - Schlagdetektion
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10404

  • Duration (semester)

    1

Ausgewählte Kapitel der Digitalen Technologien 1
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10418

  • Duration (semester)

    1

Ausgewählte Kapitel der Digitalen Technologien 2
  • WP
  • 2 SWS
  • 6 ECTS

  • Number

    10419

  • Duration (semester)

    1

Ausgewählte Softwaresysteme - Programmierung IV
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10402

  • Duration (semester)

    1

Automotive Systems
  • WP
  • 2 SWS
  • 5 ECTS

  • Number

    10434

  • Duration (semester)

    1

Bewegungsanalyse
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10432

  • Duration (semester)

    1

Bildgebende Verfahren der Medizintechnik 1
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10405

  • Duration (semester)

    1

Bildgebende Verfahren der Medizintechnik 2
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10415

  • Duration (semester)

    1

Cyber Security 1
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10423

  • Duration (semester)

    1

Cyber Security 2
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10430

  • Duration (semester)

    1

DSVM
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10413

  • Duration (semester)

    1

DT Ergänzung
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10401

  • Duration (semester)

    1

Digitale Signalverarbeitung 2
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10414

  • Duration (semester)

    1

Digitale Signalverarbeitung für (Mobil-)Kommunikationssysteme
  • WP
  • 2 SWS
  • 6 ECTS

  • Number

    10420

  • Duration (semester)

    1

Digitalfilter
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10436

  • Duration (semester)

    1

EM Design
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10428

  • Duration (semester)

    1

Einführung in die Radartechnik
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10445

  • Language(s)

    de

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h

Learning outcomes/competences

Knowledge and understanding:

  • Be able to perform requirements analysis and specification, design, implementation, testing and commissioning of mobile apps
  • Know, understand and assess software engineering challenges for mobile app development
  • Processes, Know and be able to apply processes, activities, methods, techniques, languages and tools for mobile app-specific requirements engineering
  • Know and be able to apply processes, activities, methods, techniques, languages and tools for designing mobile apps
  • Processes, activities, methods, techniques, languages and tools for designing the interaction options and screen pages of a mobile app
  • Know and be able to apply processes, activities, methods, techniques, languages and tools for implementing mobile apps
  • Processes, Know and be able to use activities, methods, techniques, languages and tools for testing mobile apps
  • Know and be able to use processes, activities, methods, techniques, languages and tools for going live with mobile apps

Use, apply and generate knowledge:

  • Development and creation of mobile app-specific development and results documents
  • Independent development of a mobile app across all development phases: from requirements engineering to commissioning (go live)
  • Presentation of the developed and achieved results

Communication and cooperation:

  • Teamwork in groups of four in the internship over an entire semester

Scientific self-image:

  • Efficient and effective implementation of mobile app-specific processes and activities
  • Practical application of suitable mobile app-specific methods, techniques, languages and tools

Contents

The aim and content of the course is to teach suitable methods, concepts, techniques, languages and tools to professionally conceptualize, design, develop, test and commission mobile business 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 and the individual screen pages,
  • Implementation of mobile apps,
  • Testing of 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, selected requirements, conception, design, development and testing activities are carried out in teamwork in order to develop a mobile app independently.

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
  • Concluding presentation

Participation requirements

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

Forms of examination

    - Development of a requirement-specific mobile app
    - Creation and upload of all central development artefacts
    - Two milestones (middle and end of the lecture period) each worth 50 points with presentations of the respective (interim) results

Requirements for the awarding of credit points

passing both milestones (middle and end of the lecture period) with at least 4.0 (sufficient) or 25 points. 

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.

Einführung in die Robotik
  • WP
  • 4 SWS
  • 3 ECTS

  • Number

    10431

  • Duration (semester)

    1

Einführung in die mobile Robotik
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10425

  • Duration (semester)

    1

Embedded Systems Hardware Design and Rapid Prototyping
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10421

  • Duration (semester)

    1

Extended Reality
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10429

  • Duration (semester)

    1

Extended Reality 2
  • WP
  • 4 SWS
  • 6 ECTS

  • Number

    10433

  • Duration (semester)

    1

Grundlagen der Mensch-Computer-Interaktion
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10424

  • Duration (semester)

    1

IoT-Netze und Protokolle
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10440

  • Duration (semester)

    1

IoT-Protokolle
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10435

  • Duration (semester)

    1

Mathematik Ergänzungen 1
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10406

  • Duration (semester)

    1

Mathematik Ergänzungen 2
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10412

  • Duration (semester)

    1

Medizinische Signalverarbeitung
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10403

  • Duration (semester)

    1

Neuronale Netze und Deep Learning
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10417

  • Duration (semester)

    1

RMS anerk.
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    RMS

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h

Learning outcomes/competences

In this course, complex and adaptive systems for problem solving are discussed and implemented. Students acquire various skills in the process.

 

Technical and methodological competence:

After the students have attended the course

  • are able to develop and analyze problem solutions with adaptive systems
    • .
  • use the most important concepts of adaptive and adaptable information systems to explain systems.
    • use methods of Computational Intelligence for the design of adaptive systems.
  • implement adaptive systems on the basis of the models explained.
    • to evaluate the systems created, where possible.
  • recognize the limits of adaptive systems.
Interdisciplinary methodological competence:
The student is able to recognize that methods of adaptive systems can be used to describe properties of technical but also business and social systems and to analyze their behavior.

Social skills:
Cooperation and teamwork skills are trained during the practical phases. Students develop practical implementations in teams of size 2 and 3 and are able to present the developed solution together.

Contents

  • Basics and examples of adaptive and complex systems and their application to control systems, networks and the web
  • Modeling of adaptation processes using various adaptive techniques
  • Application of soft computing methods (including evolutionary algorithms, particle swarm optimization, ant colony optimization, fuzzy logic, neural networks and modern machine learning methods) for system adaptation to (context) changes
  • Personalization and modelling of user profiles and context
  • Application of data classification methods in decision support systems (including rating systems, collaborative and social recommendation systems)
  • Model-based self-adaptive systems
  • Current applications of adaptive systems in the context of computer science and medical informatics

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

  • written examination paper or oral examination (according to the current examination schedule)

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

RMS anerk.
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    RMS

  • Duration (semester)

    1

  • Contact time

    60 h

  • Self-study

    90 h

Learning outcomes/competences

After successful participation in the module:
  • the students have understood the proof principle of complete induction and can apply it.
  • the students are familiar with the Cartesian representation of complex numbers and can apply the basic arithmetic operations to complex numbers.
  • the students know the concept of functions and can determine and name the properties of functions.
  • the students are able to determine the limit behavior of sequences, series and functions.
  • the students are able to determine Taylor series and approximate functions with the help of Taylor polynomials.
  • can differentiate and integrate functions and use this knowledge in applications (e.g. extreme value calculations, de l'Hospital's rule, area calculations).
  • know functions in higher dimensions. They can determine extreme points of these functions and calculate multidimensional integrals.

Contents

  • Number ranges, full induction
  • Functions: Polynomials, rational functions, exponential and logarithmic functions, trigonometric functions and their inverse functions, and other elementary functions
  • Convergence of sequences and series
  • Limit values and continuity of functions, calculation of zeros of functions
  • Differentiability of functions; one- and multidimensional 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 and more variables (antiderivative, partial integration, substitution rule)

Teaching methods

  • Lecture in interaction with the students
  • lecture-accompanying exercise
  • active, self-directed learning through tasks and accompanying materials

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 remember basic knowledge of the content covered. In addition, they should be able to transfer and apply this knowledge to new issues.
Duration: 90 minutes.
 

Requirements for the awarding of credit points

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

The performance is considered at least sufficient if at least 50% of the possible points are achieved in both the basic part and the entire examination.

Applicability of the module (in other degree programs)

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

Literature

  • Forster, O.: Analysis 1, Wiesbaden, Springer Spektrum, 2023, 13. Auflage.
  • Forster, O.: Analysis 2, Wiesbaden, Springer Spektrum, 2025, 12. Auflage.
  • Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 1 , Wiesbaden, Springer Vieweg, 2024, 16. Auflage.
  • Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 2 , Wiesbaden, Springer Vieweg, 2025, 15. Auflage.
  • Teschl, G. & Teschl, S.: Mathematik für Informatiker Band 2, Wiesbaden, Springer Vieweg, 2014, 3. Auflage

Regulatorische Grundlagen für Medizinprodukte - Teil I
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10437

  • Duration (semester)

    1

Regulatorische Grundlagen für Medizinprodukte - Teil II
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10438

  • Duration (semester)

    1

Robotik
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10410

  • Duration (semester)

    1

Robotik 1
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10442

  • 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

Robotik 2
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10443

  • 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.

Sensorik
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10411

  • 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

Smart Mobility
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10439

  • Duration (semester)

    1

  • Contact time

    30 h

  • Self-study

    45 h

Learning outcomes/competences

Interdisciplinary methodological competence:

  • The participants know professional 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).
  • The students can apply these across disciplines
    • .

Self-competence:

  • The participants are able to use learning methods, communication and presentation techniques, creativity and problem-solving techniques as well as methods of time and self-management profitably for themselves in their studies and work.

Social skills:

  • The participants know techniques for effective collaboration in groups.
  • Students know how to present content in groups.
  • Students are familiar with creativity and problem-solving techniques for groups.

Contents

The course includes modules on the following topics:

  • Learning techniques and learning types
  • Working techniques (literature research in the library)
  • Time and self-management
  • Motivation
  • Communication techniques and collaboration
  • Creativity and problem-solving techniques
  • Burnout
  • Basics of scientific work
  • Mentoring discussions (include questions about choosing a course of study, organizing studies, individual time and learning planning, dealing with difficult situations and preparing 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
Begründung zur Teilnahmeverpflichtung

Die Studierenden sollen durch die Lehrveranstaltung in die Lage versetzt werden, verschiedene Lern-, Arbeits-, Kommunikations- und Selbstmanagementechniken in ihrem Studium und beruflichen Alltag anzuwenden. Das Erlernen dieser Kompetenzen erfordert durch ihre Natur sowohl eine intensive Zusammenarbeit mit und persönliche Anleitung durch die jeweiligen Dozent/-innen, als auch eine Vielzahl praktischer Arbeiten in der Gruppe unter aktiver Supervision durch die Dozent/-innen. Um diese Ziele zu erreichen, ist eine Mindestanwesenheitspflicht in dieser Lehrveranstaltung erforderlich.

 

Softwareentwicklung robotischer Systeme mit ROS
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10444

  • 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'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

  • 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

Systembiologie 1: biologische Netzwerke
  • WP
  • 2 SWS
  • 3 ECTS

  • Number

    10426

  • 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

  • explain the structure, functionality and programming of microcontrollers (incl. interrupts, timers, PWM)
    • .
  • explain scheduling procedures and preemptive multitasking in embedded systems as well as the use of FreeRTOS.
    • describe and understand the functionality of sensors, A/D conversion and their sources of error.Explain D/A conversion and the control of DC motors.
  • Describe power management strategies and low-power modes in microcontrollers.
  • Explain debugging tools such as GDB and OpenOCD.

Use, application and generation of knowledge

  • Programming and controlling microcontrollers (interrupts, timers, PWM)
    • .
  • implement scheduling strategies and preemptive multitasking and configure a real-time operating system such as FreeRTOS
  • Integrate sensors, troubleshoot error sources and perform D/A conversion and DC motor control
    • .
  • implement power management strategies in software and test embedded software with debugging tools.
    • implement practical application examples (e.g. autonomous robotics).

Communication and cooperation

  • communicate and document technical solutions clearly
  • work in teams on projects and present results
    • .

Scientific self-image / professionalism

  • Evaluate and optimize embedded software solutions
    • .
  • to consider ethical implications in the development of embedded systems
    • .
  • to reflect on and scrutinize developments in embedded systems.

Contents

  • Microcontroller:
    • Design and structure of a typical microcontroller
    • Programming and control: interrupt control, timer/counter, watchdogs, capture/compare, PWM
    • Scheduling methods for embedded systems with and without an operating system
    • Preemptive multitasking and static priorities in embedded systems
    • Introduction to FreeRTOS and building a simple real-time operating system
  • Sensor technology:
    • Active and passive sensors
    • A/D conversion and signal processing
    • Transfer functions of sensors and their influence on the measurement results
    • Systematic and statistical sources of error in sensor measurement and their effects
    • Error propagation in sensor systems
  • Actuator technology:
    • D/A conversion and control of DC motors
    • Application of actuators in embedded systems
  • Energy-efficient software development:
    • Power management strategies for software
    • Utilization of sleep and low-power modes in microcontrollers to save energy
  • Monitoring, debugging and test strategies:
  • Use of JTAG, SWD and debugging tools such as GDB and OpenOCD
  • Debugging embedded software
  • Internship and application examples:
  • Introduction to the internship board and practical implementation
  • Basics of autonomous robotics
  • Real-time control in practical examples (e.g. motor control and sensor integration)

    • Teaching methods

    Lecture in interaction with the students, in which theoretical principles are taught and illustrated using blackboard notes and projections. This is supplemented by practicals and exercises accompanying the lectures, in which students work on practical programming tasks alone or in teams. Project work is also carried out, the results of which are presented in a final presentation. The courses include practical applications of embedded systems in realistic scenarios

    Participation requirements

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

    Forms of examination

    Written examination paper [scope: 100%] (90min); examinations during the semester (bonus points)

    Requirements for the awarding of credit points

    Passing a 90-minute graded written exam with a minimum grade of sufficient (4.0)

    Applicability of the module (in other degree programs)

    Bachelor's degree in computer science

    Literature

    • Berns, K., Schürmann, B., Trapp, M.: Eingebettete Systeme, Systemgrundlagen und Entwicklung eingebetteter Software, Vieweg+Teubner, 2010.
    • Brinkschulte, U., Ungerer, T.: Mikrocontroller und Mikroprozessoren, Springer, Berlin, 2010.
    • Fraden, Jacob: Handbook of modern sensors: physics, design, and applications,
      Springer-Verlag New York, Inc., 5th ed., 2015.
    • The FreeRTOS Reference Manual, http://www.freertos.org/, Amazon.com, 2017.
    • Douglass, B. P.: Design Patterns for Embedded Systems in C, Newnes Elsevier, 2011.
    • Brandes, U.: Mikrocontroller ESP32, Rheinwerk Technik, Bonn, 2020
    • ausgewählte Datenblätter von Sensor- und Mikrocontroller-Herstellern (werden in der Veranstaltung bekannt gegeben)

    Systembiologie 2: Systemtheorie
    • WP
    • 2 SWS
    • 3 ECTS

    • Number

      10427

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h

    Learning outcomes/competences

    Technical and methodological competence:

    • Know the definition of a DBS and the schema architecture of a DBMS
      • .
    • Develop, normalize and implement relational models 
      • .
    • Know and apply the transaction concept.
    • Know and apply SQL commands for setting up, storing and querying information (DDL, DML, DRL, DCL).
    • Perform administration of database systems by way of example.
    • Develop stored functions, procedures and triggers.

    Social skills:

    • Developing, communicating and presenting relational models and database programs in teams of two
      • .
    • Collaboratively creating and evaluating learning posters or review questions on the course content.

    Professional field orientation:

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

    Contents

    • Database and transaction concept
    • Relational model, normalization and operations
    • SQL Data Definition Language and Database Integrity
    • SQL Data Manipulation Language
    • SQL Data Retrieval Language
    • SQL Views
    • Roles and rights management
    • Stored functions, procedures and triggers
    • Backup and recovery

    Teaching methods

    • seminar-style teaching with flipchart, smartboard or 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 tasks, sample solutions and accompanying materials
    • Exercises or projects based on practical examples
    • mini-exams during the semester for regular feedback
    • 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 exam consists of two parts:
    • written examination paper, 60-90 minutes, accounting for 80% of the overall grade
    • project-related work with documentation and presentation as semester-accompanying examination performance with a share of 20% of the overall grade

    Requirements for the awarding of credit points

    • passed examination consisting of written examination paper and project-related work, which together are assessed with an overall grade of 4.0 or better

    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

    • Beighley, L., SQL von Kopf bis Fuß, O'Reilly, 2008.
    • Kemper, A., Wimmer, M.; Übungsbuch Datenbanksysteme, Oldenbourg; 2. aktualisierte Auflage, 2009.
    • Saake, G., Sattler, K., Heuer A., Datenbanken - Konzepte udn Sprachen, 6. Auflage, mitp, 2018.

    5. Semester of study

    Fachpraktikum 2 Informationstechnik
    • PF
    • 5 SWS
    • 5 ECTS

    • Number

      10350

    • Duration (semester)

      1

    Projektorientiertes Arbeiten 1
    • PF
    • 4 SWS
    • 4 ECTS

    • Number

      10340

    • Duration (semester)

      1

    Seminar Informationstechnik
    • PF
    • 4 SWS
    • 5 ECTS

    • Number

      10300

    • Duration (semester)

      1

    Web Protokolle und Services
    • PF
    • 4 SWS
    • 10 ECTS

    • Number

      10321

    • Duration (semester)

      1

    6. Semester of study

    Bachelor Arbeit und Abschluss-Kolloquium
    • PF
    • 4 SWS
    • 15 ECTS

    • Number

      101

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      120 h

    Learning outcomes/competences

    This module combines courses that are not offered regularly on various topics of practical computer science. 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)

    Master's degree in Computer Science

    Literature

    siehe Zusatzdokument zur konkreten Veranstaltung

     

    Praxis-/Auslandssemester
    • PF
    • 4 SWS
    • 30 ECTS

    • Number

      10360

    • Duration (semester)

      1

    • Contact time

      60 h

    • Self-study

      90 h

    Learning outcomes/competences

    Providing basic knowledge in the field of virtualization and cloud computing. Theoretical knowledge of architectures and technologies in this area and awareness of their strengths and weaknesses in various areas of application. Consolidation of specialist knowledge using practical laboratory tasks with currently relevant cloud services and technology platforms.

    Technical and methodological expertise:

    • Learning the relevant technical terms in the field of virtualization and cloud computing
    • Classification and evaluation of the various concepts and architectures
    • Installation and configuration of simple virtual systems with different technologies
    • Conception and practical setup of simple cloud services with open-source and commercial resource management systems
    • Overview of traditional and new areas of application for virtualization and cloud computing
    • Overview of current research topics and evaluation of scientific publications

    Contents

    • Virtualization of CPU, memory and network components
    • Container technology
    • Current virtualization and container platforms
    • Resource management and orchestration
    • Current resource management and orchestration platforms
    • Cloud computing service models (IaaS, PaaS etc.)
    • New areas of application for virtualization and cloud computing (edge computing, NFV etc.)
    • Open source development processes and communities

    Teaching methods

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

    • 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'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 Dual

    Literature

    • Thomas Erl, Zaigham Mahmood, Ricardo Puttini; Cloud Computing; Prentice Hall; 2013
    • K. Chandrasekaran; Essentials of Cloud Computing; CRC Press; 2015

    Projektorientiertes Arbeiten 2
    • PF
    • 2 SWS
    • 15 ECTS

    • Number

      10380

    • Duration (semester)

      1

    Notes and references

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