- Degree
- Master of Science
- Course location
- Garching b. München
- Teaching language
- • English
- Languages
- 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.
- Full-time / part-time
- • full-time
- Programme duration
- 4 semesters
- Beginning
- Winter and summer semester
- Application deadline
- Winter semester: 1 January to 31 May
Summer semester: 1 September to 30 November
- Tuition fees per semester in EUR
- 6,000 EUR
- Additional information on tuition fees
- Please refer to the following website for more information on tuition fees at TUM: https://www.tum.de/en/studies/fees/tuition (https://www.tum.de/en/studies/fees/tuition).
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- 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.