Data Science in Business and Economics - Master

New program starting winter semester 2019/2020.

Data Science is a vibrant, interdisciplinary and rapidly growing field.

Data scientists must be able to acquire and understand complex and unstructured data, they must be able to interpret the meaning of the results, and they must be able to communicate the results to relevant stakeholders. Hence, Data Science requires a unique combination of (1) econometrics and statistics, (2) programming skills, and (3) domain knowledge.

This four-semester M.Sc. program reflects these requirements for a unique skill set, and students who enroll in this programm specialize in econometrics and they select from a broad set of modules on different aspects of business and economics. On top of that, they enroll in modules on data science techniques, which includes programming in R and python as well as the possibility to enroll in courses in Machine Learning in collaboration with the computer science department.

Areas of Specialization

• Econometrics
• Data Science Techniques
• Business and Economics

For more information check the webpage of our faculty.

Admission is subject to a competitive selection procedure that includes individual interviews with faculty members. Shortlisted candidates from overseas will be interviewed in a video conference via Skype.

Application deadline: 15 May.
Interviews with shortlisted applicants are scheduled for mid-June.
Letters of admission will be sent out by late June - early July.
Our programs start at the beginning of October.

Find more information on the admission process on our website.

We publish all news concerning the application process on our website so you can stay in the loop.

Initially, only applications and admissions for the first semester are possible.

Admission to the M.Sc. in Data Science in Business and Economics requires a Bachelor’s degree in Business Studies or Economics or a comparable degree with excellent grades. Applicants are expected to have a solid intermediate level knowledge in Statistics / Mathematics / Econometrics, Business Administration and Economics.

Further, applicants must have experience in writing code in a statistical programming language (preferrably R or Python). Applicants can prove their experience

• by showing that they have successfully passed modules in their qualifying degree that involve students' writing code (preferrably R or Python), or
• by providing documents that demonstrate their skills/experience in writing code in a statistical programming language (preferrably R or Python), e.g., part of a B.Sc.-thesis, or
• by providing other documentation that establishes the applicant's skills/experience in writing code in a statistical programming language (preferrably R or Python)

For more information check the webpage of our faculty.

The program is free of tuition fees for all EU residents. The state of Baden-Württemberg has introduced fees for international non-EU students and second-degree students. For background information and for fee exemption options, please refer to this link.

Applicants must be fluent in German and English.

Foreign applicants must demonstrate their abiliy to study in German by submitting one of the following two certificates: DSH-2 or TestDaF 4*4*4*4. Applicants with a German Bachelor Degree do not need to provide proof of their German language skills.

For more information check the webpage of our faculty.

More and more firms and institutions are hiring data scientists, and data scientist has been America's top job for the third year according to Glassdoor.

Graduates will also find themselves well-positioned to pursue a Ph.D. subsequent to this M.Sc. program. Towards this end, students may study this M.Sc. program on a Ph.D. track, putting themselves on a fast track to a doctoral degree in Business and Economics. See also the school's Doctoral Programs.

Here you will find information about the Orientation Week for new students and valuable hints for getting a good start into your studies.

Find more information about welcome events of our faculty here.

Academic Advisory Service

Nauklerstraße 47
72074 Tübingen

Examination Office

Haußerstraße 11
72076 Tübingen

Exam Regulations

Module Handbook

Here you will find information about the exchange programs of the university.

FFW Tübingen