Welcome to our International Master's Program in Machine Learning! The University of Tuebingen collaborates closely with the Max Planck Institute for Intelligent Systems and the Max Planck Institute for Biological Cybernetics and they form together one of leading research hubs for machine learning in Europe and world-wide. This manifests in several recent initiatives: the Cyber Valley, the Excellence Cluster ``Machine Learning: New Perspectives for Science'', the TUE AI Center (BMBF Competence Center for Machine Learning) and the International Max Planck Research School for Intelligent Systems. These initatives provide plenty of opportunities for research as well as industry contacts for the students of our master program. Below, you will find all the information you will need.
Notifications regarding the winter semester 2019/2020 have been sent out. Please note that due to the large number of applications we cannot provide a detailed justification for every rejection. Late applications are not allowed and we will not answer such requests. The next intake will be for the winter semester 2020/2021 with application deadline around end of april 2020.
- Tentative course list for the winter semester 2019/2020
- New Bosch AI Campus planned for Tübingen
- ICML Best Paper Award for Researchers from Tübingen
- 27 papers at ICML and CVPR 2019 from Tübingen
More news can be found here.
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 example. Only the three lectures Deep Learning, Statistical Machine Learning and Probabilistic Inference and Learning are mandatory for every one. 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 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 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.
The deadline for applications for the Machine Learning Master program starting is April 30th.
All students, including those holding a Bachelor’s degree in Computer Science, need to submit an application. The requirements are listed below.
The studies program is taught annually, starting in winter semesters.
Please apply online for admission to the Master’s program here.
Note that after the online application you have to send your application per mail to the university (details are given at the end of the online process). In the exceptional case that you are not able to send your documents per mail, please send with ML Master in the title per email (in a single PDF, maximal 10MB) to: ml-sekretariat (applications which have not finished the online process will not be processed). @inf.uni-tuebingen.de
Note that non-EU citizens have to pay 1500 Euros per semester in addition to the regular semester fees of about 158 Euros (this includes the semester ticket for the use of all buses in Tuebingen). A list of exceptions to these tutition fees can be found here.
Admission requires a degree with a grade average of at least 2.3 (german system 1,0 is best); the degree must have been obtained in subjects related to machine learning, i.e. computer science, mathematics, physics, and related fields. Moreover, since machine learning requires profound focus and mathematics skills, applications must include proof of knowledge in the following fields: one- and multi-dimensional calculus, linear algebra, and either numerical mathematics or probability theory. Similarly, knowledge in programming, algorithms, and data structure is required. Finally, candidates are judged based on the level of interest and their personal fit with the program, for which we require a letter of motivation.
Good speaking and comprehension skills in the English language are a fundamental necessity for successful studies in this Master program. We accept any of the following proofs of such skills:
- German Abitur including at least 6 (G8) or 7 (G9) years of English.
- TOEFL iBT test with at least 94 points
- IELTS test with at least 7.0
- Cambridge Certificate in Advanced English (CAE)
- University entrance qualification obtained in the UK, Ireland, USA, Canada, Australia or New Zealand
The final decision is based on the overall affinity to the program.