Course Catalog

Study Program SoSe 2023

Zertifikatsstudium Grundlagen Digitaler Medien in pädagogischen Kontexten

Digitale Medien in Lernumgebungen

Course numberTitle of eventLecturer
01-15-03-IoT(a)-VInternet of Things (in English)

Lecture (Teaching)
ECTS: 6 (4)

Additional dates:
Mon. 11.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Mon. 11.09.23 09:00 - 18:00 NW1 Studierhaus
Tue. 12.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Tue. 12.09.23 09:00 - 18:00 NW1 Studierhaus
Wed. 13.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Wed. 13.09.23 09:00 - 18:00 NW1 Studierhaus
Thu. 14.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Thu. 14.09.23 - Fri. 15.09.23 (Thu., Fri.) 09:00 - 18:00 NW1 Studierhaus
Fri. 15.09.23 09:00 - 18:00
Mon. 18.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Mon. 18.09.23 09:00 - 18:00 NW1 Studierhaus
Tue. 19.09.23 09:00 - 18:00 NW1 H 3 - W0040/W0050
Tue. 19.09.23 - Wed. 20.09.23 (Tue., Wed.) 09:00 - 18:00 NW1 Studierhaus
Wed. 20.09.23 - Thu. 21.09.23 (Wed., Thu.) 09:00 - 18:00 NW1 H 3 - W0040/W0050
Thu. 21.09.23 - Fri. 22.09.23 (Thu., Fri.) 09:00 - 18:00 NW1 Studierhaus

Blockkurs nach Ende des Semester. Räume und Zeiten nach Absprache.

Dr. Andreas Könsgen
Prof. Dr. Anna Förster
Dr. Asanga Udugama
03-IBAP-CS (03-BB-711.01)Cognitive Systems (in English)
Grundlagen der Informationsverarbeitung in natürlichen und künstlichen Systemen

Lecture (Teaching)

weekly (starts in week: 1) Mon. 08:00 - 10:00 MZH 5600 Vorlesung
weekly (starts in week: 1) Wed. 08:00 - 10:00 MZH 1110 Übung
weekly (starts in week: 1) Wed. 10:00 - 12:00 MZH 1110 Übung

Thomas Dieter Barkowsky
03-IBAP-ML (03-BB-710.10)Grundlagen des Maschinellen Lernens (in English)
Fundamentals of Machine Learning

Kurs (Teaching)

weekly (starts in week: 1) Mon. 14:00 - 16:00 MZH 6200 Übung
weekly (starts in week: 1) Wed. 10:00 - 12:00 MZH 1380/1400 Vorlesung
weekly (starts in week: 1) Wed. 12:00 - 14:00 MZH 1380/1400 Übung

Additional dates:
Wed. 19.07.23 10:00 - 12:00 NW1 H 1 - H0020

Schwerpunkt: AI
Die Übungen starten in der 2. Semesterwoche.

Tanja Schultz
Felix Putze
Darius Ivucic
Gabriel Ivucic
Zhao Ren
03-IBAP-MRCAModern Robot Control Architectures (in English)

Lecture (Teaching)

weekly (starts in week: 1) Mon. 10:00 - 12:00 DFKI RH1 B0.10 Vorlesung
weekly (starts in week: 1) Thu. 14:00 - 16:00 DFKI RH1 B0.10 Übung
Robotics is a complex field that emerged at the intersection of multiple disciplines such as physics, mathematics and computer science. New advances in hardware and software design and progress in artificial intelligence enable robotics research to pursue higher goals and achieve increased autonomy in various environments. For instance, robots can operate in disaster zones for search and rescue operations, can be employed in rehabilitation and healthcare, space and underwater exploration, etc. Given the complexity of such scenarios, it is essential to develop robust robotic systems with a high degree of autonomy, able to assist humans in difficult and tedious tasks.

This course aims to provide the fundamentals of modern robot control approaches that enable robotic agents to operate in the environment autonomously. The course introduces a basic understanding of autonomous robots, along with tools and methods to control various types of mobile robotic platforms and manipulators. Firstly, the course presents the types of sensors and actuators employed in autonomous robotic platforms. Secondly, it offers a formal understanding of the robot geometry, its kinematic and dynamic models. Finally, the course provides methods and approaches to control the robotic system from a deliberative and reactive point of view. Students will put this knowledge into practice during tutorials and exercise sheets using Python implementation and robot simulations.


  • Introduction to Robotics and AI: long term robot autonomy, artificial intelligence, deliberative vs. reactive control, robotic applications.
  • Sensing and Actuation Modalities: types of sensors and actuators, sensor fusion, actuator control.
  • Robot Geometry and Transformations: robot transformations in the 3D space, exponential and logarithmic maps, forward and inverse geometric models.
  • Kinematics: definition of twists and wrenches for rigid bodies, geometric Jacobian formulation, forward and inverse kinematics.
  • Dynamics: an introduction to Lagrangian and Newtonian mechanics, robot dynamics formulation, recursive Newton-Euler algorithm.
  • Localization: direct and probabilistic methods for robot localization, odometry, global localization, particle filter.
  • Path Planning: path vs. trajectory generation, graph-based methods for path planning (e.g. Djikstra, A\*).
  • Kinodynamic Planning: transcribing a dynamic planning problem into trajectory optimization, direct and indirect methods, costs and constraints.
  • Reinforcement Learning-based Control: mathematical foundations, discrete vs continuous methods, reinforcement learning for closed-loop robot control.
  • Dynamic Control: PD gravity compensation control, computed torque control, admittance vs impedance control.
  • Optimal Control: energy-shaping control, LQR and time-varying LQR control.

Learning Outcomes

At the end of the course, the student is expected to be able to:
  • Define robot autonomy and list its key aspects.
  • Describe the sensor and actuator modalities used in robotics, and explain their relevance for robot control.
  • Implement and understand the low-level actuator control methods.
  • Compute the 3D world coordinate transformations for rigid bodies.
  • Apply the robot forward and inverse geometric model.
  • Describe a robotic system based on its kinematic and dynamic properties.
  • Use probabilistic methods for robot localization.
  • Generate an optimal path for a mobile robot or manipulator using graph search methods.
  • Plan a path taking into account the robot kinodynamic properties.
  • Use reinforcement learning methods to control simple robotic systems.
  • Apply dynamical and optimal control methods on robotic systems such that they are robust against disturbances.
  • Assess the strengths and limitations of different control methods presented in the course.
  • Identify open challenges in robotics research and current trends in state-of-the-art.
  • Communicate confidently using the terminology in the field of robotics.
  • Cooperate and work in teams in order to solve tasks.


a) Submission of 6 worksheets in groups of 4 students and group interview for final grade (Übungsaufgaben und Fachgespräch).
b) Individual oral exam without worksheet submission (mündliche Prüfung).


  • Mechanics of Robotic Manipulation, Mathew T. Masen, MIT press, 2001.
  • Algebra and Geometry, Alan F. Beardon, Cambridge University Press, 2005.
  • Modelling and Control of Robot Manipulators, Lorenzo Sciavicco, Bruno Siciliano, Springer, 2000.
  • Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), Sebastian Thrun, Wolfram Burgard, and Dieter Fox, MIT Press, 2005.
  • Introduction to Autonomous Mobile Robots, Siegwart R., Nourbakhsh I., Scaramuzza D., MIT press, 2011.
  • Automated Planning: Theory and Practice, Malik Ghallab, Dana Nau, Paolo Traverso, Elsevier, 2004.
  • Behaviour-based robotics, R. C. Arkin, MIT press, 1998.
  • Modern Robotics: Mechanics, Planning, and Control, Kevin M. Lynch and Frank C. Park, Cambridge University Press, 2017.

Frank Kirchner
M. Sc. Mihaela Popescu (Organizer)
03-IMAA-CTHCICurrent Topics in Human Computer Interaction (in English)

Kurs (Teaching)

weekly (starts in week: 1) Wed. 12:00 - 16:00 MZH 5500 Kurs

Profil: DMI
Schwerpunkt: IMA-DMI, IMA-VMC

Prof. Dr. Tanja Döring
Dr. Susanne Putze
03-IMAA-EC (03-MB-804.03)Entertainment Computing (in English)

Lecture (Teaching)

weekly (starts in week: 1) Tue. 12:00 - 14:00 MZH 6200 Vorlesung
weekly (starts in week: 1) Tue. 14:00 - 16:00 MZH 6200 Übung

Profil: DMI
Schwerpunkt: IMK-DMI, IMA-VMC

Prof. Dr. Rainer Malaka
Dr. Thomas Münder
03-IMAP-DIS (03-MB-703.02)Design of Information Systems (in English)

Lecture (Teaching)

weekly (starts in week: 1) Mon. 12:00 - 14:00 MZH 6200 Vorlesung
weekly (starts in week: 1) Tue. 08:00 - 10:00 MZH 1380/1400 Übung

Profil: SQ.
Schwerpunkt: IMVP-DMI, IMVP-SQ
Die Veranstaltung ist inhaltlich identisch mit "Entwurf von Informationssystemen" (keine Doppelanerkennung möglich).

Martin Gogolla
03-IMS-AISSeminar on Autonomous and Intelligent Systems (in English)

Seminar (Teaching)

weekly (starts in week: 1) Tue. 16:00 - 18:00 DFKI RH1 A1.03 Seminar

Profil: KIKR

Frank Kirchner
Melvin Laux
03-IMS-APMSK (03-ME-711.09)Ausgewählte Probleme der multisensorischen Kognition (in English)
Selected Problems of Multisensory Cognition

Seminar (Teaching)

weekly (starts in week: 1) Thu. 12:00 - 14:00 CART Rotunde - 0.67 CART 0.01 (Besprechungsraum) Seminar

Profil: KIKR, DMI.
Die Veranstaltung findet in Englischer Sprache statt.

Christop W. Zetzsche
Kerstin Schill
03-IMVA-ACSSApplied Computer Science in Sports (in English)

Kurs (Teaching)

weekly (starts in week: 1) Wed. 14:00 - 16:00 MZH 1110 Vorlesung
weekly (starts in week: 1) Wed. 16:00 - 18:00 MZH 1110 Übung

Schwerpunkt: IMVA-AI, IMVA-DMI
The aim of this course is to create an understanding of the major aspects of sports applications. The course is split into two parts: the first half has a classic lecture/tutorial style, whereas the second half will focus on the creation of individual sports applications.

The lectures will explain the necessary fundamentals, such as sensor technology, user feedback, and the conduction of empirical studies, along with a number of inspiring examples.

In the project part, own prototypes for sports applications are developed in small groups. The exact application as well as the technical implementation approach can be chosen freely. The final graded outcome of the course will be a small sports application about which a presentation has to be held and a documentation in a scientific paper style has to be written.

The course will be held in English.

Schwerpunkt: AI, DMI

Robert Porzel
Dr. Tim Laue
Bastian Dänekas
03-IMVA-EI (03-ME-899.03)Embodied Interaction (in English)

Kurs (Teaching)

weekly (starts in week: 1) Thu. 08:00 - 10:00 MZH 5600 Kurs
weekly (starts in week: 1) Thu. 10:00 - 12:00 MZH 5600 Kurs

Profil: DMI.
Schwerpunkt: IMVA-DMI, IMVA-VMC

Robert Porzel
Prof. Dr. Rainer Malaka
03-IMVA-MAD (03-ME-804.06)Mobile App Development (in English)

Lecture (Teaching)

weekly (starts in week: 1) Mon. 12:00 - 14:00 SFG 0150 Vorlesung
weekly (starts in week: 1) Mon. 14:00 - 16:00 SFG 0150 Übung

Profil: DMI
Schwerpunkt: IMVA-DMI
Die Veranstaltung richtet sich an Studenten der Informatik und Digitalen Medien. In Gruppenarbeit sollen die Studierenden semesterbegleitend ein App-Projekt umsetzen. In der Vorlesung werden alle relevanten Informationen der modernen Softwareentwicklung, mit Fokus auf die mobile App-Entwickung, vermittelt. Dazu gehören Themen wie mobiles Testing, Scrum, UX Design, Evaluation & Nutzertests, Design Patterns und Cross-Plattform-Entwicklung. Das Ziel dabei ist die Vermittlung von praxisrelevantem Wissen aus dem Alltag eines erfolgreichen Unternehmens.

Prof. Dr. Rainer Malaka
David Ruh
Nicolas Autzen
03-IMVP-ECLEdge Computing Lab (in English)

Kurs (Teaching)

weekly (starts in week: 1) Mon. 16:00 - 18:00 MZH 4140 Kurs

Peter Fereed Haddawy
Prof. Dr. Anna Förster
Thomas Dieter Barkowsky
09-60-M8/9-RRituals in Digital Games (in English)
Gruppe A

Seminar (Teaching)

weekly (starts in week: 1) Tue. 10:00 - 12:00 SpT C4180 (2 Teaching hours per week)

Dr. Dominic Ford
09-70-B.2-2Community Formation in Digital Games (in English)

Seminar (Teaching)

weekly (starts in week: 1) Thu. 16:00 - 18:00 SpT C4180

Communities that form around digital games and gaming have become increasingly significant. We may have heard of the ‘toxic’ communities of competitive games like League of Legends, the very young community of Roblox or Minecraft, the friendly history nerds of the Total War series, and so on. Perhaps most impactfully, GamerGate showed us that gaming communities can have very serious and far-reaching consequences. On the other hand, game communities formed around games like Animal Crossing: New Horizons and Among Us at the beginning of the pandemic demonstrated that they can also be a lifeline in difficult and uncertain times. In this seminar, we will focus on how these communities are formed and maintained. We will examine three crucial aspects of community formation: the affordances of particular games, the strategies developers use to create and engage with communities (or not), and the players themselves.

Dr. Dominic Ford
10-76-6-WD2-02Key Topics in Linguistics: The language of computer-mediated communication (in English)

Seminar (Teaching)

weekly (starts in week: 1) Thu. 12:15 - 13:45 GW2 A3390 (CIP-Labor FB 10) (2 Teaching hours per week)

Additional dates:
Mon. 17.07.23 09:00 - 16:00 SFG

In this course, we will explore different genres of computer-mediated communication, including social networking sites, (micro-)blogs, online comments, and online reviews. We will consider the social practices that occur in these genres, and discuss the ways in which language is variously shaped, re-worked, and constrained by them. Throughout the semester, we will investigate concepts such as identity construction, intertextuality, anonymity and privacy, multimodality, and multilingual practices, to name a few. You will work on small assignments throughout the semester to get hands-on experience with researching digital discourse and social practices online.

By the end of the course, you will be able to
• explain central concepts relevant to the field of CMC
• apply research methods in CMC
• evaluate ethical issues related to CMC
• analyze digital discourse
• describe digital practices across genres and platforms

Jones, R. H., Jaworska, S., & Aslan, E. (2020). Language and media: A resource book for students (2nd ed.). Taylor & Francis.
Page, R. E. et al. (2022). Researching language and social media: A student guide (2nd ed.). Routledge.
Tagg, C. (2015). Exploring digital discourse: Language in action. Routledge.

Dr. Ramona Kreis
10-M80-2-ExMo1+2-07Mixed-methods for research on multimodal data: visual, audiovisual, and verbal (in English)
Modultyp B/C im Studiengang Language Sciences, M.A.

Seminar (Teaching)

weekly (starts in week: 1) Tue. 12:15 - 13:45 MZH 1460 (2 Teaching hours per week)

In this course empirical methods for the analysis of varied media will be introduced and then developed specifically in the context of selected audiovisual, visual and verbal media. A specific focus will be placed on examining to what extent such media products 'tell stories', either deliberately or by accident, and the consequences of such stories for their reception by audiences. One particular area of concern will be narratives that (either intentionally or unintentionally) 'disinform' their audiences by setting up narrative expectations of various kinds. These kinds of uses will be addressed empirically in concrete analysis. The course meshes broadly with an ongoing research project on 'fake narratives', whose progress can be followed at: Participants will be encouraged to engage with the method of analysis being developed in this project and so receive firsthand experience in research methods. The qualitative and quantitative methods introduced are, however, generally applicable to many research questions and media. Dedicated sessions will introduce several of the empirical quantitative methods that can be employed for improving the reliability and generalisability of qualitative studies regardless of research question.

Prof. John Bateman, Ph.D.