The Data Science MSc course at the University of Potsdam offers broad and interdisciplinarily structured training in methods and is characterized by a strong emphasis on practice and research. The interdisciplinarily structured master's degree in data science combines content from computer science, mathematics, information systems, and the natural sciences. Core courses provide you with an overarching understanding of machine learning and deep learning, statistical data analysis, data assimilation, business analytics, and big data infrastructures. More specialized courses help you engage with the current state of research for the areas of your choosing.
In seminars, you will work through complex topics, and in the module of applied data science, you will apply, in practice, the competences you have acquired. In the research module, you will be connected to a research project at the University of Potsdam or one of Potsdam's many research institutions. An industry internship is also possible as an option. Berlin/Potsdam's lively start-up scene and many big data companies offer ample opportunities for internships.
- Data scientists are in equally strong demand in many areas of the economy and in research. Career paths exist in areas where large quantities of big data are created that can serve as the basis for decision-making, prognoses, and intelligent action. These include, for example, online commerce; search machines; the finance sector; the automobile, pharmaceutical, and manufacturing industries; meteorology; and climate research.
- The master's degree offers you an accordingly large number of possible career paths. The degree prepares you for a career as a manager or highly qualified expert in a company, for founding a company of your own, or for completing a PhD and pursuing a research career in computer science, mathematics, or the natural sciences.
Get more detailsVisit official programme website
- Machine Learning
- Statistical Data Analysis
- Bayesian Inference and Data Assimilation
- Data Infrastructures and Software Engineering
- Data Science and Business Analytics
- Applied Data Science
- Computer Engineering for Big Data
- Computational Foundations of Data Science
- Research Data Management, Law and Ethics
- Applied Data Science Internship
- Advanced Problem Solving Techniques
- 24 months
Start dates & application deadlines
- Apply before
DisciplinesBusiness Intelligence & Analytics Data Science & Big Data Machine Learning View 23 other Masters in Business Intelligence & Analytics in Germany
We are not aware of any academic requirements for this programme.
We are not aware of any English requirements for this programme.
- Applying for a master's degree generally requires you to hold an undergraduate degree, such as a bachelor's degree. A first degree in either computer science or mathematics qualifies you in any case for this master's degree. A degree in information systems or natural sciences qualifies you if your first degree strongly emphasized content from the areas of computer science or mathematics. Depending on your background, bridge modules can be complete gaps in the other respective discipline. The program additionally requires proof of good English-language skills corresponding at least to the B2 level of the Common European Framework of Reference for Languages.
InternationalFreeTuition FeeBased on the tuition of 0 EUR per year during 24 months.
EU/EEAFreeTuition FeeBased on the tuition of 0 EUR per year during 24 months.
- 280 Euros per semester administrative fee
Living costs for Potsdam
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
Apply and win up to €10000 to cover your tuition fees.
Updated in the last 6 months
Check the official programme website for potential updates.