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The interdisciplinary field of data science deals with methods for using data to automatically produce knowledge, insights, and models for prognosis, risk, and action. The master's degree program, which is taught in English, connects machine learning, statistical data analysis, natural scientific methods of data assimilation, and business analytics. The program offers broad and interdisciplinarily structured training in methods and is characterized by a strong emphasis on practice and research.
| Name | Data Science |
| Degree | Master of Science |
| Standard period of study | 4 semesters |
| Credit points | 120 |
| Language of instruction | English |
| Start of study (1st semester) | Winter semester |
| Campus | Golm |
| Fees & Charges | Semester fees and charges: yes Tuition fees: no |
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Program Content
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.
Course Objective and Future Career Options
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; meteorolgy; 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.
Prerequisites for Admission to the Master’s Program
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. We strongly recommend that your prior studies included preliminary courses in probability and statistics. 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 complete gaps in the other respective discipline. The program additionally requires proof of good English-language skills corresponding at least to the C1 level of the Common European Framework of Reference for Languages.
You can find the exact prerequisites for admission in the subject-specific Admission Regulations for the master's degree program in data science.
Program Structure
In the four-semester master's program, you earn a total of 120 credit points, consisting of the following modules and your master's thesis: for additional information, please consult the subject-specific Degree Regulations or the Departmental Advisory Office.
Modules | Credit points |
|---|---|
| Mandatory modules | 48 CP |
| Machine Learning | 9 CP |
| Statistical Data Analysis | 9 CP |
| Bayesian Inference and Data Assimilation | 9 CP |
| Data Infrastructures and Software Engineering | 6 CP |
| Data Science and Business Analytics | 9 CP |
| Applied Data Science | 6 CP |
| Elective modules | 42 CP |
| Research module | |
| Research module A or B | 12 or 15 CP |
| Advanced modules | |
| Advanced Machine Learning A, B | 9 or 6 CP |
| Advanced Statistical Data Analysis A, B | 9 or 6 CP |
| Advanced Data Assimilations and Modeling A, B | 9 or 6 CP |
| Advanced Infrastuctures and Software Engineering A, B | 6 CP |
| Advanced Business Analytics A, B | 9 or 6 CP |
| Advanced Applied Data Science A, B | 9 or 6 CP |
| Mathematical Foundations of Data Science A, B | 9 or 6 CP |
| Computer Engineering for Big Data | 6 CP |
| Computational Foundations of Data Science | 6 CP |
| Research Data Management, Law and Ethics | 6 CP |
| Applied Data Science Internship | 12 CP |
| Advanced Problem Solving Techniques | 9 CP |
| Bridge modules | 12 CP |
| Foundations of Computer Science | 6 CP |
| Foundations of Stochastics | 6 CP |
| Master's Thesis | 30 CP |
| Total | 120 CP |
Contact
Department of Computer Science
Maria Alegre Moral and Dr. Henning Bordihn | Departmental Advising
- +49 331 977-314032
- counsellorucs.uni-potsdampde
Campus Golm
Building 70, Room 1.50
Advantages at a Glance
The English-language master's degree program is characterized by a unique interdisciplinary combination of machine learning, statistical data analysis, natural scientific methods of data assimilation, and business analytics. You may choose your more specialized subjects yourself. The University of Potsdam is a leading center of research in data science. The Collaborative Research Center "Data Assimilation", for example, investigates the integration of data and natural scientific models in cognitive neurosciences, biophysics, and earth sciences. The degree program opens up excellent career opportunities for you in research, established companies, and the start-up scene.
The University of Potsdam has taken into account the actual conditions among students and introduced the option for part-time study into several degree programs. This also pertains to Data Science. For more information, go to part-time studies at the University of Potsdam.
Application
Have you decided for a Master's Program in Data Science at the University of Potsdam? Then you should take the next step on the application pages to find out more about current application and enrollment procedures.
Contact
Department of Computer Science
Maria Alegre Moral and Dr. Henning Bordihn | Departmental Advising
- +49 331 977-314032
- counsellorucs.uni-potsdampde
Campus Golm
Building 70, Room 1.50
Important Links
Frequently Asked Questions
Study and Examination Regulations
Application
Admission Regulations
This description is based in part on information from the subject-specific regulations for a master’s degree in Data Science at the University of Potsdam dated December 17, 2018 (AmBek No. 03/2018, p. 138).
