Admission requirements
The master's degree course 'Data Science' can only be started in winter semester. Admission requirements are:
Basic knowledge of linear algebra, calculus, statistics, and programming
Bachelor’s degree or a comparable qualification
Proof of English language skills at the B2 CERF level or a comparable qualification
Basic knowledge of the German language (A2 level), proof of which can be provided at a later stage of the first year of studies.
This master’s degree course is about…
The master’s degree course Data Science takes an interdisciplinary approach, recognising that data-driven solutions are applicable across a wide range of fields and industries. By combining core principles from statistics, computer science, mathematics, and domain-specific knowledge, this degree course equips students with the tools and expertise needed to tackle complex problems in various domains such as healthcare, finance, business, engineering, and social sciences.
What students can expect
Compulsory modules
- Mathematics of Artificial Intelligence
- Machine Learning
- Fundamentals of Artificial Intelligence and Data Science
- Databases
- Bayesian Modelling
- Interdisciplinary Data Science
- Interdisciplinary Projects
- Master's Dissertation
Compulsory Elective Modules
- Deep Learning and Generative Artificial Intelligence
- Machine Learning for Time Series
- Fundamentals of Natural Language Processing
- Software Engineering for Data Science
- Bayesian Econometrics
- Computational Physics
- Multivariate Statistics
- Data Structures and Efficient Algorithms
- NoSQL Databases
- Natural Language Processing
- Software Engineering
- Biometry
- Algorithms and Programming