Master Data Science​

Program Structure

Table of Contents

Degree Content

The curriculum is divided into a foundational area with about 44-64 CP, a seminar (5 CP), a practical course (7 CP), and an area of specialization with about 14-22 CP, plus some room for „additional competences“ with maximum 12 CP. Courses offered in the specialisation area form the basis of the final thesis with 30 CP. Following the idea of the Integrated Interdisciplinary University, the final thesis can be written not only in the core fields computer science and mathematics, but also in one of the following application fields: Business Analytics (BA), Computational Life Science (CLS), Computational Social Science (CSS), and Physics (P).


Area CP Courses
Foundational Area
  • Introductory Courses (mandatory): Introduction to Data Science (6 CP), Mathematics of Data Science (9 CP)
  • Elective Core Courses
  • Basic Courses from Computer Science and Mathematics
  • Data Science Ethics (mandatory): Ethics, Technology, and Data (4 CP)
Additional Competences0-12 
  • Wide range of electable courses from the university’s program
  • Seminar (5 CP)
  • Practical Course (7 CP)
Specialisation Area including Master’s Thesis44-52Specialisation Area: 14-22 CP

Master’s Thesis: 30 CP
  • Specialisation area: Computer Science, Mathematics, Computer Science and Mathematics
  • Application area: Business Analytics, Computational Life Science, Computational Social Science, Physics
  • Lecture courses
  • Master thesis (30 CP)

The foundational area covers the main methodological foundations of data science. It consists of a list of selected modules from computer science and mathematics, among them the introductory modules „Introduction to Data Science“ and „Mathematics of Data Science“. An additional part of the core area is the module „Ethics of Data Science“.

As „additional competences“, students have the possibilities to choose up to 12 CP in courses from a wide range of areas, for example a language course or a non-technical subject.

The second part of the curriculum is the specialisation area, leading towards the final master’s thesis. While the specialisation areas „Computer Science“, „Mathematics“, and „Computer Science and Mathematics“ focus on strong methodological competences, a specialisation in one of the application areas, as listed above, enables students to work on applied data science problems in the context of another discipline.

Note: If you want to chose physics as your application area, all competences from the profile physics must be met. For more information, have a look at the prerequisites.

Comprehensive Examination Regulations

Regulations that apply in principle to all Bachelor’s and Master’s degree programs, as well as detailed information on proof of the required language skills, can be found in the Comprehensive Examination Regulations of RWTH. Examination regulations are published only in German due to their legally binding nature.

The subject-specific examination regulations regulate the legally binding study objectives, study requirements, study procedure and examinations. In its appendix, it contains the description of the modules that make up the course of study. Examination regulations are published only in German due to their legally binding nature.

Therefore, an inofficial translation for the core area and additional competences can be found below.

Core Area

The official rules for the Core Area are specified in the examination regulations. Below is an inofficial translation.

In the Core Area you need to take courses for 44-64 credit points (CP) from Mathematics, Computer Science and Ethics. There are some mandatory courses, and some elective courses. The Core Area has its own catalogue of elective courses, which you can find in RWTHonline. The following description only refers to the Core Area. Do not confuse it with the Focus Areas Mathematics or Computer Science.

  • In Ethics there is only the mandatory course Ethics, Technology, and Data (4 CP).
  • In Mathematics you have to take the mandatory course Mathematics of Data Science (9 CP). You need at least 18 CP of core courses in mathematics. This means you have to take elective core courses in mathematics for at least 9 CP.
  • In Computer Science you have to take the mandatory course Introduction to Data Science (6 CP). You need at least 18 CP of core courses in computer science. This means you have to take elective core courses in computer science for at least 12 CP.

Adding up the minimum requirements of 4 CP from ethics, 18 CP from mathematics, and 18 CP from computer science, you have 40 CP. Which
means that you need to take at least 4 CP more of elective courses (from mathematics or computer science).

Additional Competences

The rules for the area additional competences are defined in the official exam regulations.
Here are some (inofficial) informations in English.

You can use 0-12 CP for the area „additonal competences“ (in particular, this area is optional). The credits from this area count for the 120 CP that are required for completing the degree. The grades, however, do not count for the overall grade.

The purpose of the area „additonal competences“ is to give you the opportunity to study non-technical courses that you are interested in, or to gain basic competences from mathematics or computer science that you are missing (because one can join the Data Science program with a background from computer science, mathematics, or physics, students have different basic knowledge in these areas).

More specifically:

  • You can take a language course offered by the university for up to 4 CP. These courses are offered by the language center. Please contact them directly with any questions concerning the language courses.
  • You can take non-technical courses offered at RWTH Aachen, for example, from history, philosophy, economics, social sciences up to 6 CP. There is (currently) no list of such courses. You have to browse the courses in RWTHonline yourself and see if you find something that is of interest to you.
  • Additionally, you can take bridge courses or basic bachelor courses in math or computer science depending on your background:
    • If you joined the M.Sc. Data Science with the profile „computer science“, then you can take bridge courses or basic bachelor courses from math as additonal competences.
    • If you joined the M.Sc. Data Science with the profile „mathmatics“ or „physics“, then you can take bridge courses or basic bachelor courses from computer science as additonal competences.

In particular, courses that are offered in the core or specialization areas of Data Science cannot be taken as additional competences.

For registration of non-technical courses that you want to take as additional competences, you should contact the organizers of the course. For some courses you can use „free registration“ in RWTHonline, but anyway the organizers of the course should know your status as participant.

If you pass the exam in such a course, then the organizers should give you a paper certificate, which can then be sent to the ZPA to be added to your additional competences.

In general, your choices for additional competences have to be approved by the academic advisor (except for the language course).


Seminar selection

Students must make sure to not miss the seminar and lab selection deadline (usually around January for the following summer term and around June for the following winter term).

Seminars introduce students to academic research and writing and allow students to learn more about a specific area in software engineering. Students must complete one mandatory seminar worth 5 CP.

Students can choose from a broad variety of seminars offered by the many chairs and research groups of the Computer Science department of RWTH Aachen University.

Individual curriculum

The students in the Data Science master program are not provided with a pre-defined curriculum / study schedule. Students are responsible for organizing their curriculum themselves and they have to ensure that in the end they meet the program’s required structure as described above.

This enables students to compose their own curriculum focusing on their individual interests in the area of Data Science (within the mentioned limits). For the specialization area, the students can choose from the respective module catalogs. The majority of modules rarely change, but from time to time courses are added, replaced, or removed from the catalogs. Note that most modules in the catalogs are offered either in summer terms or in winter terms. Additionally, students need to consider that not all modules yield the same amout of credit points.

Most of the elective modules are offered in English allowing students that are not proficient in German to study the Data Science master program with many courses to choose from. There may be few elective modules that are in German only and Data Science students are free to choose these as well.

Exceeding a subject area’s credit point limit

Each subject area has an upper limit for the credit points ensuring that Data Science master students receive a broad education in different areas of multimedia. For the Data Science curriculum, a student may not exceed a subject area’s upper credit point limit. If an elective course is completed such that the subject area’s limit is exceeded (in order of their examination dates), then the course is considered as an additional course that does not contribute to the student’s curriculum and is not counted towards the overall grade for the master.

The only exception is the focus area where it is possible to exceed the total of 22 CP through one module. Examples:

  • 4 courses with 6 CP (=24 CP) would be fully counted.
  • 5 courses with 6 CP are too many, one of them would not be counted.

Introductory Meeting

At the beginning of each semester an introdcutory meeting is held for all new Data Science students. An overview of the last meeting can be found here.

Some additional information: You can wait with registration for courses until after the meeting (registration will still be open then). But if you want, you can start registering for courses before (note, however, that some oragnizers set up registration only at the beginning of the semester). Registration does not mean that you are committed to take the course. You can register for more courses than you actually want to attend, and then see, which courses you like most. The deadline for exam registration is later, you do not need to worry about it now.

If you plan to take a German course in the upcoming semester, register until April 3 via the language center. Students of M.Sc. Data Science have a voucher for one course of 4 weekly hours (you can freely choose the semester in which to use the voucher).