Courses are held in English.
German courses specially designed for international Master's and PhD students are available at the university’s House of Languages. The full German course programme is available at: www.uni-tuebingen.de/en/1056.
30 April (for international [non-EU] citizens as well as for German and EU citizens)
Approx. 1,500 EUR per semester for students from non-EU countries
The Master’s programme in Machine Learning offers a wide choice of courses in machine learning and general computer science. Apart from a few mandatory courses, allows students to choose their subjects according to their interests. Students will attend lectures, seminars, and project lab courses under the supervision of scientists who introduce them to basic and applied research and current topics in machine learning.
To pick up on scientific trends and make the best use of the current state of research, the curriculum relies heavily on the strong research presence on site in machine learning (Max Planck Institute for Intelligent Systems, Max Planck Institute for Biological Cybernetics, Excellence Cluster "Machine Learning: New Perspectives for Science'', Tübingen AI Center, Cyber Valley, IMPRS for Intelligent Systems) as well as in the wider field of computer science. Top-level researchers in all major methodological branches of machine learning are present in Tübingen – personnel that will actively engage in teaching the Master’s programme in Machine Learning. (See CSRankings for the University of Tübingen and note that the Max Planck Institute for Intelligent Systems is located in Tübingen as well.) Since the field is obviously very young and currently developing extremely rapidly, training will naturally be based on the most recent insights and the most pressing research questions of these teaching researchers. Project work and the Master’s thesis will offer students the opportunity to develop code for research purposes and their own scientific projects.
As interdisciplinarity is an important aspect, the Master’s thesis can be supervised by a professor of any subfield of computer science.