FsB vom 06.04.2018 mit Änderungen vom 01.07.2019, 02.03.2020, 21.03.2023 und 10.12.2024
Due to the constant increase in data volumes and data complexity, Data Science has created a new, interdisciplinary field of work that covers a wide range of aspects of data analysis, such as handling large amounts of data, statistical modelling, visualisation, pattern recognition with machine learning methods, but also ethical and legal questions. Data Scientists are urgently needed for many socially significant developments, e.g. in the areas of intelligent vehicles or housing, artificial intelligence or social media.
The extraction of information from data is a genuinely interdisciplinary undertaking: The data collection and the communication of the results of the analyses require a link to the domain from which the data originate. The processing and analysis of the data requires an interaction of computer algorithms with statistical methods.
In this Master’s degree programme students acquire the relevant skills for these endeavours. These include the foundations of machine learning that allow to critically assess the merits and dangers of harvesting massive amounts of data. The inclusion of classical statistical tools adds to the understanding of the limitations of artificial intelligence and data driven methods.
At graduation students have a rich tool chest at their disposal ranging from the required IT-skills to the statistical knowledge allowing for the development of new machine learning methods and the application of modern tools of data extraction in many areas. Students also learn to work in a highly interdisciplinary environment as the program is run by the Faculty of Business Administration and Economics and the Centre for Statistics (ZeSt) jointly with the Faculty of Technology. Finally the program also provides ample possibilities to discuss pressing questions concerning legal and ethical implications of modern machine learning approaches.
As a consequence the graduates are well equipped for the booming labour market longing for data science experts.
You will find the programme of lectures for this course in the eKVV.
An overview of the introductory and information events is provided by the central student counselling services.
The standard period of studies is 4 semesters.
The studies Data Science comprise 120 credit points.
Access to the Master programme is granted to those who can provide evidence that they have a first university degree which has a standard period of study of at least six semesters, qualifies for exercising a profession and is in accordance with the subject-specific regulations.
In any case, please read the specific Admission requirements for this Masters programme in the Subject-specific regulations (PDF).
Degrees from accredited Bachelor programmes at German ‘Berufsakademien’ are equivalent to Bachelor degrees from universities.
Applicants with a university degree obtained abroad are granted access provided that the degree they have acquired is deemed sufficient for this purpose and they can provide evidence of the required language skills.
Further information on required language skills
Special conditions apply to applicants with a foreign certificate of education.
The study places for this degree programme are subject to local admission restrictions (numerus clausus). You need to apply within the currently applicable application deadlines.
As soon as you receive a positive response in the application and status portal (notice of access from the faculty) and receive your admission notice from the Student Office, you can submit your application for enrolment within the set deadline.
Step by step to a Master programme with NC
To the application portal
Special conditions apply to applicants with a foreign certificate of education.
Internet pages of the subject Data Science
Internet pages of the responsible institution(s):
Faculty of Business Administration and Economics with the courses offered
Die Angaben zu Zulassungsbeschränkungen / Numerus clausus beziehen sich auf die Bewerbung zum Wintersemester 2024/25 und Sommersemester 2025. Informationen zu NC Werten aus früheren Jahren finden Sie auf dieser Seite.