International Programmes 2019/2020

Machine Learning (MSc) Machine Learning

University of Tübingen • Tübingen

Master of Science
Teaching language
  • English

Courses are held in English.

Programme duration
4 semesters
Winter semester
More information on beginning of studies
Winter semester - October
Application deadline

30 April (for international [non-EU] citizens as well as for German and EU citizens)

Tuition fees per semester in EUR
Additional information on tuition fees

Approx. 1,500 EUR per semester for students from non-EU countries

Combined Master's degree / PhD programme
Joint degree / double degree programme

The Master’s programme 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 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 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 for the Master’s programme 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 of any subfield of computer science.

Course organisation

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's thesis is recommended for the fourth semester.

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Types of assessment

Written and oral exams, lab courses, scientific presentations, graded research projects, Master's thesis in the second year

A Diploma supplement will be issued
International elements
  • International guest lecturers
  • Specialist literature in other languages
Course-specific, integrated German language courses
Course-specific, integrated English language courses
The course of study can be taken entirely online
Digital learning and teaching modules
  • Video learning
  • Learning platforms, e.g. ILIAS and Moodle, are used.
Description of e-learning elements

A mixture of video lectures, additional e-learning material for individual courses, e-learning quizzes, and assignments are offered and continuously expanded.

Participation in the e-learning course elements is compulsory
Can ECTS points be acquired by taking the online programmes?
Can the e-learning elements be taken without signing up for the course of study?
Tuition fees per semester in EUR
Additional information on tuition fees

Approx. 1,500 EUR per semester for students from non-EU countries

Semester contribution
Enrolment fees at the University of Tübingen are currently about 160 EUR per semester. This includes use of local public transport free of charge from Monday to Friday in the evenings, at weekends, and on public holidays. In addition, students may purchase a semester ticket for unlimited use of public transport in the city of Tübingen and the surrounding area (currently about 100 EUR).
Costs of living
According to the Tübingen Student Services Organisation (“Studierendenwerk”), estimated basic student expenses are about 850 EUR per month, including rent for student accommodation. Rent for private accommodation will typically be more expensive.
Funding opportunities within the university
Academic Admission Requirements

Academic admission requirements include 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 (see below).

Language requirements

Applicants must provide adequate proof of English proficiency, documented by one of the following documents:

  • German Abitur certificate with proof of six (G8) or seven 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
Application deadline

30 April (for international [non-EU] citizens as well as for German and EU citizens)

Submit application to

Online application:

For questions regarding the application process, please contact the office of "Advising and Admission of International Students". E-mail:

Possibility of finding part-time employment

Students may find jobs as graduate research assistants for projects of the Department of Computer Science as well as many other research groups or companies in need of employees with computer science competence.


Accommodation is available through the student services organisation (“Studierendenwerk“) or on the private market. Rooms in student accommodation cost approx. 200-400 EUR per month. As Tübingen is a very attractive place to live, private accommodation is more expensive and can take some effort to find. To make sure you find a suitable place to live, you should start looking as early as possible.

We recommend that you apply for student accommodation through the “Studierendenwerk” at the same time that you apply for admission to the Master's programme (See: and and send in a copy of your notification of admission as soon as you have received it. (Your application won’t be processed until the “Studierenwerk” has received proof of your admission.) For further information, check out the “Studierendenwerk” pages on housing in Tübingen (

Career advisory service

The University of Tübingen offers a number of different services that offer helpful advice to those planning on studying in Tübingen as well as to students who are already enrolled here – whether they are just beginning their studies, are well into their studies, or are finishing their studies and planning a career.

Specific specialist or non-specialist support for international students and doctoral candidates
  • Welcome event
  • Accompanying programme
  • Other
Support programmes for international students
The university offers an orientation week ( for all newly arriving students in the week before the official start of the semester. For international students, this includes:
- a welcome and a "help desk" for international students
- the official welcome for international students
- the advisory programme “How to Study at the University of Tübingen”
- a wide range of social activities offered by student groups

German courses are available at the university’s "House of Languages" (, including “early bird” and evening classes for beginners, which are specially designed for international Master's and PhD students.

The student initiative “StudiT” (“Studierenden-Initiative Internationales Tübingen”) offers a buddy programme and a wide range of social activities during the orientation week and throughout the semester (,

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