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Data Science | Master

Image: GaudiLab/Tiwat K/Shutterstock.com/Antonia Leven

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.

THE PROGRAM AT A GLANCE
NameData Science
DegreeMaster of Science
Standard period of study4 semesters
Credit points120
Language of instruction
English
Start of study (1st semester)
Winter semester
CampusGriebnitzsee and Golm

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. 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.

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.

CONTENT AND CREDIT POINTS (CP)

Modules

Credit points

Mandatory modules48 CP

Machine Learning

Statistical Data Analysis

Bayesian Inference and Data Assimilation

Data Infrastructures and Software Engineering

Data Science and Business Analytics

Applied Data Science

9 CP

9 CP

9 CP

6 CP

9 CP

6 CP

Elective modules

42 CP

Research module

  • Research module A or B

Advanced modules

  • Advanced Machine Learning A, B
  • Advanced Statistical Data Analysis A, B
  • Advanced Data Assimilations and Modeling A, B
  • Advanced Infrastuctures and Software Engineering A, B
  • Advanced Business Analytics A, B
  • Advanced Applied Data Science A, B
  • Mathematical Foundations of Data Science A, B
  • Computer Engineering for Big Data
  • Computational Foundations of Data Science
  • Research Data Management, Law and Ethics
  • Applied Data Science Internship
  • Advanced Problem Solving Techniques


Bridge modules 12 CP
  • Foundations of Computer Science
  • Foundations of Stochastics

 

Master's Thesis 30 CP
Total120 CP

Contact

Department of Computer Science

PD Dr. Henning Bordihn | Departmental Advising

 

Griebnitzsee Campus | Building 04, Room 0.23

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

PD Dr. Henning Bordihn | Departmental Advising

 

Griebnitzsee Campus | Building 04, Room 0.23

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).