This seminar introduces students to practical and methodological aspects of data-driven engineering. Current topics are presented, discussed, and critically evaluated, with a focus on applying machine learning, optimization, and simulation techniques to real-world engineering problems. Example applications may include product design, industrial process improvement, and robotics or production systems.

All participants are required to write a seminar paper and give an oral presentation. Depending on the topic, an implementation of the considered models or methods using standard software libraries and tools (e.g., Python-based ML libraries, simulation environments) may be expected. 

The topics will be provided at the beginning of the seminar. All topics can serve as a foundation for further project work or a Bachelor’s thesis.

Additional Information

The seminar is offered in English. The number of participants is limited. Information on the application process is available in ILIAS.  

Organizational Information

See further details on course organization at: https://lehre.imi.kit.edu and in ILIAS.