Teaching
Courses, seminars and student projects.
Bachelor and Master thesis projects are listed on the open projects page.
Registration for courses is exclusively via CAMPO and StudOn.
Biomedical Image Analysis Project [BIMAP]
We offer projects in a structured way only in the summer semester (5 and 10 ECTS). Please apply in time for a spot, as this is highly frequented (10–12 spots and around 100 applicants per seminar). After acceptance you will receive the list of available projects and can select your priorities. We rarely provide projects aside from BIMAP.
Tracking Olympiad [TRACO]
This 5 ECTS seminar is only offered in the summer semester. In this seminar you learn to detect and track Hexbugs, voluntarily moving micro robots. More information is on the seminar's micro website.
Data Science Survival Skills [DSSS]
Lecture and exercises (2 SWS + 2 SWS), 5 ECTS, winter term only.
In DSSS we teach survival skills: knowledge that is crucial for a career in data science and for working efficiently. Topics covered intensively include:
- File formats for text, images, structured and arbitrary data
- Multithreading and multiprocessing
- Just-in-time compilation using numba
- Prototyping graphical user interfaces
- No-code environments
Fantastic datasets and where to find them [FANDAT]
Seminar (2 SWS), 5 ECTS, every semester.
In this seminar we investigate where to get (biomedical) datasets, how to look for them and how to evaluate them. What turns a dataset good or bad? How is it used in the community? And what impact do datasets have in machine and deep learning? The aim is to create your own open educational resource about a given dataset, which is then peer-reviewed by your fellow students.
Cognitive Neuroscience for AI Developers [CNAID]
Lecture (2+2 SWS), 5 ECTS, every semester.
CNAID is a lecture designed by Patrick Krauß, Andreas Maier and Andreas M. Kist. We cover the basics of cognitive neuroscience and discuss the biological implementations of neural networks, connecting biology and artificial intelligence with specific examples of how both are linked and how aspects of AI are inspired by biology.