Teaching Profile

At the Chair of Information Theory and Machine Learning, we offer a wide range of courses in the compulsory and elective areas of numerous degree programs. They are part of various compulsory and elective modules and are taught in summer and winter semesters according to the current schedule.

With courses from the subject areas of systems theory, information theory and machine learning, we are intensively involved in the basic training in the compulsory area of the degree courses in Electrical Engineering (ET), Information Systems Technology (IST), Mechatronics (MT), Regenerative Energy Systems (RES) and Biomedical Engineering (BMT). Building on this, we offer a large number of advanced elective courses, particularly in the areas of information theory, communication theory and machine learning, which are primarily designed for students on the ET and IST degree programs. We also provide students on the Nanoelectronic Systems (NES) Master's degree course with in-depth training in the field of systems theory. In addition, we also offer courses as an export service for students from other faculties, as part of the general qualification (AQUA / studium generale) and the Citizens' University (Bürgeruniversität).

By participating in the Hauptseminar of the study field of Information Technology (IT), supervising seminar projects as part of our Oberseminar and supervising student research projects and theses, we accompany and support the process of independent scientific work of our students. Our doctoral seminars are a contribution to the structured doctoral program in electrical engineering.