Mathematics in Data Science Technical University of Munich
- Duration
- 4 semesters
- Language of instruction
- English
- Tuition fees
- Tuition varies
- Next application deadline
- 30 November 2026 (summer semester)
- Language level required
- English: C1German: None
Programme overview
Quick facts
- Degree
- MSc
- Duration
- 4 semesters
- Full-time / part-time
- Full-time
- Intake
- Winter and summer semester
- Joint degree / double degree programme
- No
- A Diploma supplement will be issued
- Yes
- Combined Master's degree / PhD programme
- No
Language of instruction
The majority of courses in this Master's programme are taught in English (approximately 90%). Students can choose to write the Master's thesis in either English or German. The programme can be completed entirely in English.
Programme description
The Master's programme in Mathematics in Data Science is oriented towards students seeking a high-profile education in Mathematics with a focus on the rapidly growing fields of Data Science and Artificial Intelligence. Graduates of this programme will gain in-depth knowledge of advanced techniques for data analysis and processing, the ability to adapt complex models to real-world problems, and the skills to combine and refine these models to develop predictive and classification tools. Graduates will be qualified to assess different algorithms' capabilities and limits and to design effective solutions for specific problems.
The programme emphasises the mathematical foundations of methods and algorithms used in machine learning, statistics, optimisation, and data representation theory. It balances theoretical knowledge with practical applications in data analysis, data engineering, and machine learning.
In addition, students will take interdisciplinary classes, including foreign language training, introductory law courses, and lectures addressing the social and political dimensions of data science.
Programme structure
This two-year, four-semester Master’s programme offers a rigorous foundation in the mathematical principles underlying data science -- including data acquisition, modelling, and classification. While the programme emphasises mathematical depth, it remains flexible, allowing you to tailor your studies to your specific interests within the field.
You will take part in lectures, hands-on practical courses, and seminars, and you will also have the chance to carry out your own research. In addition to core technical content, the curriculum thoughtfully integrates courses on the social and ethical dimensions of data handling, both within the main programme and through targeted elective options.
The programme culminates in a Master's thesis during the fourth semester, allowing you to apply your knowledge in a focused research project.
Mode of study
- Fully on-site
International elements in the curriculum
The curriculum of this study programme includes international elements that support global perspectives and cross-cultural learning:
- International guest lecturers
- Integrated/optional study abroad unit(s)
Students have the opportunity to spend one or two semesters abroad as part of the programme.
Integrated internships
An internship of six weeks is to be completed as part of the Master’s programme.
Application and admission
Application period(s)
Summer semester
| Applicants from | Applications begin | Application deadline | |
|---|---|---|---|
All countries
|
1 October 2026
|
30 November 2026
|
Winter semester
| Applicants from | Applications begin | Application deadline | |
|---|---|---|---|
All countries
|
1 February 2027
|
31 May 2027
|
Academic admissions requirements
A qualified university degree in Mathematics, Computer Science (minor Mathematics), or comparable study programmes
Applicants who have obtained a Bachelor's degree from Bangladesh, China, India, Iran, or Pakistan will have to submit a GRE (General) Test. The required scores are:
Verbal reasoning: (will not be taken into account any more)
Quantitative reasoning: 157
Analytical writing: 3.5
The institutional code for the GRE is: 7806 Department 5199
For more information, see: http://www.ma.tum.de/Studium/UnterlagenMScDSEn.
Alternatively, students can submit a score card from the Indian GATE test (Mathematics). A minimum qualifying score for the respective year is necessary.
Language requirements
German language requirements
English language requirements
Accepted certificates include
| Certificates | Minimum result |
|---|---|
PTE Academic
|
Total: 65 / 90
|
Cambridge English Qualifications
|
Total: C1 Advanced
|
IELTS Academic
|
Total: 6.5 / 9
|
TOEFL iBT Home Edition (before 2026)
|
Total: 88 / 120
|
TOEFL iBT (before 2026)
|
Total: 88 / 120
|
How to apply?
Costs and funding
Tuition fees per semester
| Applicants from | Tuition fee | |
|---|---|---|
Non-EU countries
|
6,000 EUR
|
Semester contribution
Please refer to this page for more details: https://www.tum.de/en/studies/fees.
Cost of living
In order to cover personal expenses while studying in Munich, we recommend a budget of at least 900 EUR per month.
Part-time employment
Munich is a very good place to find internships or working student positions in industry, e.g. with banks, insurance, software or consulting companies, as well as in the research and development departments of large corporations.
Please refer to the following page for more details: https://www.tum.de/en/studies/during-your-studies/living-and-working/jobs-and-internships.
Scholarships and financing information
Many international students can have their fees waived or receive scholarships to finance them. You can find all information on waivers and scholarships here.
Living & services
Support for international students
- Welcome event
- Buddy programme
- Specialist counselling
- Cultural and linguistic preparation
https://www.studierendenwerk-muenchen-oberbayern.de/en/
Career advisory services
TUM Career Service: https://www.community.tum.de/en/career-service/
Accommodation
It’s not easy to find a place to live in Munich – but it’s not impossible either! The Technical University of Munich (TUM) supports students and staff in their search for accommodation by providing personal advice, in-house listings and useful information to ensure that you can quickly find a place to call your own.
For more information, see: https://www.tum.de/en/studies/during-your-studies/living-and-working/accommodations.
Contact
Department of Mathematics
- Name
- PhD Anna Veselovska
- Address
- Boltzmannstrasse 3, 85748 Garching b. München