- Degree
- Master of Science
- Course location
- Cottbus
- Teaching language
- • English
- Languages
- The programme is designed to be completed entirely in English. It is possible, however, to take additional mandatory elective classes in German if one wishes.
- Full-time / part-time
- • full-time
• part-time (study alongside work)
- Programme duration
- 4 semesters
- Beginning
- Winter and summer semester
- Additional information on beginning, duration and mode of study
- The semester begins in April for the summer semester and in October for the winter semester.
- Application deadline
- • Applicants with foreign qualifications for admission to higher education: 15 May for the following winter semester and 15 January for the following summer semester
• Applicants with German qualifications for admission to higher education: 31 August for the following winter semester and 1 March for the following summer semester
• Applicants with European Union/ European Economic Area citizenship: 15 August for the following winter semester and 15 February for the following summer semester
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- In 1987, a famous British statistician, George Box, proclaimed, “Essentially, all models are wrong, but some are useful”. Today, companies like OpenAI or Google don’t fiddle with models that might give bad predictions, they simply extract relevant information from abundant data with no use for models at all. And yet, data science is far more than just curve fitting for those who are too lazy to do the “real” science. It is real science! It is likely that physical models for numerical weather prediction or protein folding will still be needed in the future and that the natural sciences will not cease to exist. What we are currently seeing is only the beginning of the integration of data mining and powerful large language models with models from physics, chemistry or biology, with no end in sight!
The MSc programme in Mathematical Data Science features comprehensive training in the mathematical foundation of Data Science algorithms. This includes courses in non-convex optimisation and numerical simulation, numerical linear algebra, stochastic processes, high-dimensional statistics, or graph theory, but also courses that provide the computer science fundamentals, such as neural networks, distributed computing, cryptography, or information retrieval. The core curriculum is accompanied by numerous courses from related application fields, such as AI, computational neuroscience, control engineering, cybersecurity, or bioinformatics, where you will learn how to apply data science algorithms.
Studying at a small technical university, with many courses shared between different study programmes, you will quickly get in touch with students from other disciplines (e.g., engineering, economics). You will also learn about their projects and the numerous opportunities at BTU Cottbus-Senftenberg to apply data science methods to do cutting-edge research in energy systems, neuroscience, or sustainable technologies.
If you are an international student, you will have the opportunity to take German language courses, which gears you up for a future career in industry or the public sector. (German speaking students may learn another language.)
The rewards for studying Mathematical Data Science are excellent career opportunities in academics, industry or the public sector, with application fields ranging from IT and technology to health care, finance, consulting, or resource management.
For more information, please visit our page: https://www.b-tu.de/en/math-data-science-ms (https://www.b-tu.de/en/math-data-science-ms).