The purpose of this seminar is to help you to broaden your expertise in Machine Learning (ML) and Artificial Intelligence (AI) and apply it to selected real-world use cases.

Therefore, we will introduce selected ML/AI technologies and tools to you, which are relevant for your chosen seminar projects. You will acquire hands-on experience with these tools and apply them to real-world scenarios on realistic data sets. Please bear in mind: to allow you access to real-world data, some of the data sets might require you to either sign-up on a webpage, agree to follow data handling steps, sign a data use or confidentially agreement, or similar aspects. We will equip you with the required ML/AI expertise and provide you access to materials for your chosen projects. We expect you to deep dive in the required ML/AI technology, to do research on related work in the specific field, to design and apply your own ML/AI approach, and to evaluate your approach and compare it to results from related work. As a result, you will broaden your ML/AI skills on a real-world digital health use case, apply selected ML/AI methods, and evaluate and interprete your obtained results.

You will select your project preference from a list of seminar topics presented in the kick-off event. We will coach you throughout the whole semester with regards to the chosen project, i.e. you will have regular appointments with your tutor. Furthermore, we will provide guidance for improving your research and presentation skills throughout the seminar. Therefore, you will share your results in an intermediate and a final presentation with all participants. The presentation will help you to communicate your approach and intermediate results as well as to receive individual feedback on the approach and progress. Ultimately, you will document your findings in a scientific report at the end of the seminar.