Admission to the international Master’s program in Machine Learning is not admission-restricted, but all students, including those holding a Bachelor’s degree in Computer Science, are requested to submit a formal application.
Application deadline for international (non-EU) citizens as well as German and EU citizens: 30 April
A Bachelor's degree (or equivalent) in either computer science, mathematics, physics or related natural sciences with a grade of at least 2.3 (German grading system). In particular, competences from the following areas are required, equivalent in content and scope to those in the BSc course in Computer Science in Tübingen:
- Mathematics: one- and multidimensional analysis, linear algebra and either numerics or stochastic
- Computer science: Programming, Algorithms and Data Structures.
Applicants must also provide adequate proof of English proficiency.
Courses are held in English. Applicants must provide adequate proof of English proficiency, documented by one of the following documents:
- German Abitur certificate with proof of 6 (G8) or 7 years (G9) of English language instruction
- TOEFL iBT test with at least 94 points
- IELTS test with a score of at least 7.0
- Cambridge Certificate in Advanced English (CAE)
- Higher education entrance qualification from Great Britain, Ireland, USA, Canada, Australia, New Zealand
The Machine Learning program cannot be complemented with a minor subject.
The international 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.
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 from any subfield of computer science.
Our International Master's program in Machine Learning has opened its doors in the winter term 2019/2020.
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)
- 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.
The course consists of four major study areas: Foundations of Machine Learning, Diverse Topics in Machine Learning General Computer Science and Expanded Perspectives. In the first semester Mathematics for Machine Learning, and Data Literacy are recommended modules, followed by Statistical Learning, Probabilistic Inference and Learning and Deep Learning in the next semester. At least one practical course and one seminar are recommended for the second or third semester. The master thesis is recommended for the fourth semester.
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 bioinformatics and its application to the life sciences. This includes a critical discussion of research goals, contents, proposals, and research problems, and requires a high scientific level.
Erasmus-Programme (e.g. Uppsala, Schweden)
In jedem Studiengang ist ein freiwilliger Auslandsaufenthalt möglich. Mit der Planung sollte ca. ein bis eineinhalb Jahre vor der Abreise begonnen werden.
Weitere Informationen und Beratung zum Auslandsstudium finden Sie auf der fachübergreifenden Seite Wege ins Ausland. Zudem bieten einige Fächer auch eigene Informationen zu Auslandsaufenthalten an.
Computer science in Tübingen is one of the leading CS departments in Germany in terms of research, and it is internationally renowned. The department collaborates with major enterprises and research institutes both nationally and internationally. The CS department places strong emphasis on interdisciplinary cooperation with other university departments, in particular medicine, biology, psychology, and media studies, and also with the three Max Planck Institutes located in Tübingen.Zahlen und Fakten:
In the winter term 2020/21 about 2090 students study at the Department of Computer Science:
- Bioinformatik Bachelor of Science: 107
- Bioinformatik/Bioinformatics Master of Science: 122
- Bioinformatik Promotion: 32
- Informatik Bachelor of Science Hauptfach: 676
- Informatik Bachelor of Science Nebenfach: 68
- Informatik Master of Science: 257
- Informatik Promotion: 110
- Informatik Bachelor of Education: 75
- Informatik Bachelor of Education berufl LA: 2
- Informatik Master of Education: 9
- Informatik Vorleistungen Erweiterungsfach: 6
- Erweiterungsprüfung: 6
- Informatik Lehramt: 1
- Kognitionswissenschaft Bachelor of Science: 243
- Kognitionswissenschaft Master of Science: 126
- Kognitionswissenschaft Promotion: 19
- Machine Learning Master of Science: 22
- Medieninformatik Bachelor of Science: 143
- Medieninformatik Master of Science: 53
- Medizininformatik Bachelor of Science: 89
- Medizininformatik/Medical Informatics Master of Science: 15
Entscheidungshilfe bei der Studienwahl
Entscheidungshilfen für ein Erststudium
Die Universität Tübingen bietet einen Online-Studienwahltest an. Anhand verschiedener Tests und Fragebögen können Sie überprüfen, welche Studiengänge der Universität Tübingen zu Ihnen passen.
Die Universität bietet darüber hinaus weitere Hilfen zur Entscheidungsfindung an. Dazu gehören z.B. der Besuch von Lehrveranstaltungen, Orientierungsveranstaltungen zu Studienwahlthemen sowie verschiedene Beratungsangebote. Weitere Hinweise finden Sie auf den Seiten für Studieninteressierte.
Entscheidungshilfen für Masterstudiengänge
Bei der Studienwahlentscheidung für die Masterstudiengänge spielen Spezialisierung, Schwerpunktsetzung und forschungs- sowie berufsbezogene Kriterien eine Rolle. Für Interessierte an Masterstudiengängen gibt es eine Vielzahl an Orientierungshilfen wie z.B. den Besuch von Lehrveranstaltungen und spezielle Beratungs- sowie Informationsangebote (z.B. Zentrale Studienberatung, Studienfachberatung, Career Service). Nähere Informationen finden Sie unter Beratung und Information.
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.
Depending on the course selection, the master program qualifies for doctoral studies in Computer Science. For further information see the website Faculty of Science - Doctoral Studies.