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Data Analytics (M.Sc.)

Taught in German


Foto: pitinan/



Data science is a highly relevant and interdisciplinary field of research and work which links computer science, mathematics and domain knowledge. The analysis of large pools of data, e.g. using methods of artificial intelligence and machine learning for the extraction of useful information has become an integral part of today's society and a number of career fields. If a stronger focus is applied to computer science and domain knowledge, we find ourselves in the field of data analytics.

The Master's degree program "Data Analytics" is aimed at Bachelor's students who wish to expand the domain knowledge they acquired in their Bachelor's degree, which is not related to computer science, with skills in the field of data science, i.e. mathematics and computer science, and thus become capable of in-depth scientific work in the field of data analytics. This programme is accessible to students with a Bachelor’s in the following fields:

  • Economics
  • Natural Sciences
  • Life Sciences
  • Engineering
  • Agricultural Sciences
  • Environmental Sciences
  • Nutritional Sciences

However, students with other Bachelor’s degrees (e.g. Humanities and Social Sciences) may also be permitted to enroll following an inspection by the board of examination.

This course of study expands upon the students‘ domain knowledge gained during the bachelor’s programme. During the first year of studies, the programme primarily focuses on methods of modern data analysis, including basic concepts of computer science, data base programming, aspects of information and data management, basic methods of artificial intelligence, as well as the fundamentals of data analysis and visualisation. The second year of studies covers a project phase and the Master Thesis, which combines domain knowledge with these methods of data analysis.

"Data Analytics" is offered as a hybrid degree programme, allowing students to study in person, entirely digital or a combination of the two. This also applies to projects and the Master’s Thesis. Students may switch at any time, including during the lecture period. Furthermore, the content of lectures, tutorials and seminars is made available digitally and asynchronously.


WiSe, kein NC


Duration of Studies: 4 Semesters

Duration of Studies:

4 Semesters - 120 Credit Points (CP)

Composition of the Study Programme

Composition of the Study Programme

The course of studies encompasses 120 CP and is divided into 14 compulsory modules, including one project module (9 CP), a specialisation module (12 CP) and the Master Thesis module (30 CP). Because Data Analytics if offered as a hybrid programme, students have the option to study in person, entirely remote, or in a mixed format.

The first year of studies provides an introduction to the basics of Data Analytics. This includes learning the programm languages Python and R, as well as the basics of information technology and data bases.
Basic methods of artificial intelligence are also introduced during the first semester,as they will need to be applied for data analysis during the second semester. Another essential tool is text mining, which is used for the collection and analysis of data.

Moreover, first-year students are to attend the lecture series "Data Science", in which (working groups) at JLU introduce themselves. This not only provides students with a great overview of the range of topics, but also with the opportunity to establish connections for future projects or the Master Thesis. The first year of study is accompanied by two modules on information and data management, in which important aspects of data (long-term archiving, ethical and legal aspects, repositories, version control and much more) are examined.

In addition to a module on information visualisation, the third semester includes a project phase in which students deepen their basic knowledge. The specialisation module can build on the "Project Data Analytics" module and further develop a project; it is intended to prepare students for the Master's thesis. The Master's thesis itself constitutes the entirety of the fourth semester.


Semester 1 Semester 2
Information technology

Advanced Data Analytics

Basics of programming and visualization in Python

Introduction to Data Analysis in R

Artificial Intelligence

Text mining

Lecture series: Data Science

Introduction to data bases

Information and data management I

Information and data management II

Semester 3 Semester 4
Visualization of Information Master Thesis 

Project Data Analytics

Specification Module  


There is also a part-time option for an 8-semester degree programme. This can be found in the University of Giessen's programme announcements (MUG).


Application: Entrance Requirements

Commencement of Studies

Only possible during the Winter Semester.

Entrance Requirements

The requirement for acceptance into the Master’s course is a Bachelor’s degree with completed modules of at least 6 CP in statistics, as well as 90 CP in a field of science besides computer science and mathematics.

Other courses of study can be approved upon examination by the board of inspectors.



Application / Enrollment

No NC (GPA) requirements apply to this course of study.

Start of Enrollment for the Winter Semester of 2024/25
  • 01.06.2024
End of Enrollment for the Winter Semester of 2024/25
  • 01.09.2024 for applicants with a german university entrance qualification
  • 15.08.2024 for applicants with a foreign university entrance qualification

Different rules may apply to international applicants. Read more.

Career Options

Career Options

Doctoral Studies

  • Doctorate possible after the successful completion of the Master's degree.

Career Fields

The demand for STEM graduates in the field of computer science and data analysis is already high and will continue to rise massively in the coming years. This applies to almost all branches of industry, banks, insurance companies and public authorities, as well as many areas of the natural sciences, humanities, cultural studies, social sciences and life sciences.

Data analytics focuses on analysing data in order to create knowledge from it. This approach, also known as data mining, is currently becoming increasingly important in all areas of business, industry, administration and research. In the future, it will be almost impossible to be successful in these areas without utilising data analytics experts. These people work at the interface between the specialised discipline and computer science. Overall, this opens up a wide range of employment opportunities in almost all modern sectors of the economy as well as in public administration and research.



Information for outgoing students

Information and consultation


Information for incoming students

Information and consultation



Subject Advisor
Subject Advisors

Prof. Dr. Christian Heiliger

Institute for Theoretical Physics
Heinrich-Buff-Ring 16, room 441
35392 Gießen
Phone: 0641 - 99 33360
E-mailChristian Heiliger


Beate Pitzler
(Student counselling)

Student Hotline "CallJustus"
(Initial information on all questions relating to the degree programme, Phone: 0641-9916400)

International Office - Contact Persons and Office Hours
(Counselling and support for international students and applicants)