Digital Society Initiative
This course offers an introduction to and reflection on machine learning (ML) from the viewpoints of different disciplines. The students become familiar with the basic methods subsumed under the term ML and understand their potential, limitations, and suitability for different problem types. Concrete ML use cases from Medicine, Law, Linguistics, Physical Sciences, Robotics, Theology and other areas are introduced. Exercises will allow students to solve in small interdisciplinary groups ML problems from these diferent areas.
This interdisciplinary module is designed for Master's students of all faculties with an interest in ML.
Friday 10.00 - 12.00 (lecture)
Friday 13.00 - 14.00 (exercise)
(No exercise on 23.12.2022)
The course will be held in English.
Assessment / ECTS Credits
The module is passed if 50% of the exercises are reasonably solved. The exercises will be evaluated weekly and discussed in the following session.