Students holding a good Bachelor’s degree in Computer Science, Mathematics, Physics or an equivalent degree, and who are interested in current machine learning research and modern methods may continue their studies to obtain a Master’s degree. Please see the admission requirements below.
The Master’s program in machine learning offers a wide choice of courses in computer science and, apart from a few mandatory courses, allows students to choose their subjects according to interest. 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.
Here you find three potential plans how to study:
- theory profile
- biomedical applications
- industry applications
Note that these are only examples! Only the three lectures Deep Learning, Statistical Machine Learning and Probabilistic Inference and Learning are mandatory. The rest of the program can be chosen very flexible with minimal formal requirements.
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 as well as 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 for the Master’s Program Machine Learning. Since the field is developing rapidly, training will be based on the most recent insights. Project work and the Master’s thesis will offer students the opportunity to diver deeper into specific research questions and applications.
As interdisciplinarity is an important aspect, the Master’s thesis can be supervised by a professor of any subfield of computer science.
Program Goals and Objectives
The Master’s program in machine learning is research-oriented and will enable graduates to analyze, implement, leverage, and modify techniques of machine learning. Education in problem solving capabilities is a central training objective.
Students have the opportunity to advance their knowledge and skills to a level which will allow them to get involved in top national and international research in machine learning and its many applications in the sciences as well as in engineering and other fields. This includes a critical discussion of research goals, contents, proposals, and research problems, and requires a high scientific level.
Career Opportunities and Prospects
Due to very fast technological developments in handling large amounts of data and apply findings in a wide variety of applications, there is an ever growing need for specialists in machine learning. Since this is a highly demanding area, a PhD degree is often required. Graduates in this international Master's program will be competent in all basic and many advanced areas of machine learning, understanding and suitably applying this increasingly essential tool for dealing with large datasets, be it in science, industry or alternative domains. The studies program deals both with generic methods and their applications to specific fields, making it highly relevant for new career and job market purposes. In this whole Master program, besides professional expertise, graduates will also acquire language skills and intercultural competence due to the program’s international nature – another requirement of the international job market, both in academia and without.