Data Science M.Sc.

 

Data Science is a hot topic, which gains in importance as a cross-sectional topic almost everywhere including natural sciences, engineering, and medical science.

Data Science deals with the extraction of knowledge and usable information from data. The available data sets are often very large, heterogeneous, and partially unreliable. Data Science is an interdisciplinary field with its roots in computer science, mathematics, and statistics and it has a strong link to various application areas.

The essential constituents of data science are data analysis and systems engineering.

Therefore, this course of study is going to convey modern methods of data analysis as well as algorithms and techniques for the development of information systems.

The students are provided the possibility of specialization within the framework of an application area:

• Computer Science
• Mathematics
• Computer Science and Mathematics
• Business Analytics
• Computational Life Science
• Computational Social Science
• Physics

 

Degree Content

The curriculum is divided into a foundational area with about 60 CP and an area of specialization with about 30 CP, plus some room for “additional skills” with a maximum of 12 CP. Courses offered in the specialization 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, abbreviated BA, Computational Life Science abbreviated CLS, Computational Social Science abbreviated CSS, and Physics, abbreviated P.

Curriculum
Core Area 44-64 CP	Introductory lectures, mandatory Introduction to Data Science, 6 CP; Mathematics of Data Science, 9 CP
	Required electives Foundational lectures in mathematics and computer science
	Mandatory module: Ethics, Technology, and Data, 4 CP
Additional Skills 0-12 CP	Courses freely chosen from among the broad range of RWTH offerings
Seminar, Lab Course 12 CP	Seminar, 5 CP; Lab Course, 7 CP
Specialization Area 14-22 CP including Master’s Thesis 30 CP	Computer Science CS	Mathematics M	Computer Science and Mathematics CSM	Application Area BA, CLS, CSS oder P
	Lectures
	Master’s Thesis

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, Technology, and Data".

As "additional skills", students have the option of choosing 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 specialization area, leading towards the final Master's thesis. While the specialization areas "Computer Science", "Mathematics", and "Computer Science and Mathematics" focus on strong methodological competences, a specialization in one of the application areas, as listed above, enables students to work on applied data science problems in the context of another discipline.

Find more information on the course of study homepage.

 

Prerequisites

The program builds on the Bachelor’s degree programs in mathematics or computer science. It requires a Bachelor’s degree in mathematics, computer science, physics, or a related area. You can find more information about the prerequisites on the course of study web page.

The required educational background is formulated in the examination regulations. The examination board determines whether the entry requirements are fulfilled.

 

Career Prospects

Data-Science methods are used in a broad spectrum of applications in science and industry.

Data science gains increasing importance in the industry due to the desire and the need for utilizing the information that becomes available because of the comprehensive networking of terminal equipment - Internet of Things, Industry 4.0 - the widespread use of social networks and the availability of immense amounts of measurement, multimedia and simulation data. In addition to the companies from ICT, financial and service sectors, also "classical" industrial companies look for graduates with this qualification profile.

Data Science is also a hot research topic, which gains in importance as a cross-sectional topic almost everywhere including natural sciences, engineering, and medical science.

 

Module Handbook and Examination Regulations

The module handbook provides a description of all modules of a degree program and offers a comprehensive insight into the program contents.

The examination regulations are comprised of legally binding provisions on learning objectives, prerequisites for study, the course structure and processes, and examination procedures.

Regulations that generally apply to all Bachelor's and Master's degree programs, including information on language proficiency requirements, can be found in RWTH's General Examination Regulations. These general regulations are further specified and complemented by the subject-specific examination regulations.

If two examination regulations are valid for a degree program during a transition phase, the most current version shall apply to students enrolling in the program for the first time.

Please note that only the German examination regulations are legally binding.

Module Handbook
Subject Specific Examination Regulations
RWTH's General Examination Regulations

 

Faculty

The Master course of study in Data Science is offered by the Department of Computer Science and the Department of Mathematics in the Faculty of Mathematics, Informatics, and Computer Science.