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M.Sc. Data Science in Business and Economics

Why Data Science?

Data Science is a vibrant, interdisciplinary, and rapidly growing field. According to the World Economic Forum, AI and big data are the top job skills on the rise. Consequently, studying cutting-edge AI and machine learning technologies is not only intellectually stimulating - it also equips students with essential qualifications for impactful careers in industry, policy, and academia.

Why Business and Economics?

Domain knowledge is key to identifying the right questions, selecting relevant data, applying suitable analytical methods, and communicating insights effectively to stakeholders. Simultaneously the rise of AI technologies, such as Large Language Models, highlights the need for decision makers in business and economics to possess a good understanding of their capabilities and limitations in a particular use case.

Why this program?

This four-semester M.Sc. program is designed for students who have built domain knowledge in business and economics during their Bachelor’s studies and now seek to complement it with a comprehensive set of data science skills. The program offers a unique combination of: (1) AI, machine learning, and econometrics, (2) programming and computational skills, and (3) deepening of domain expertise. These are the key features of the program:

compulsory training in Data Science Project Management, which includes programming in Python and R
deepening of econometrics as well as business and/or economics skills
flexible choice of modules on Data Science Techniques ranging from hands-on courses implementing AI in business settings to machine learning theory courses at the computer science department
the Data Science Project where students design and execute a data science project in small teams

The majority of our graduates is either hired as Data Scientist/Analyst in industry or pursues a PhD.

What is the Data Science Project?

A unique element of the program is the Data Science Project, which is typically part of the third semester. Student teams design and execute a data science project including data collection, data cleaning, modeling and analysis, and presentation. The final product is usually an App or a dashboard allowing the user to explore the problem and the solutions. Example projects include the following:

Itinerary AI planning city trips tailored to user preferences
a navigation app that helps users choose the safest routes during nighttime
a model to pinpoint potential locations for solar parks on underutilized land
an integrated machine-learning pipeline to identify heat islands in urban cities

Why Tübingen?

The University of Tübingen, along with its surrounding ecosystem, stands out as a leading hub for Machine Learning and AI research in Europe. It is home to notable institutions such as the Machine Learning Cluster of Excellence, the Tübingen AI Center, the Max-Planck-Institute on Intelligent Systems, and Cyber Valley. This creates a great environment rich in advanced research, diverse study programs, and a wealth of institutions dedicated to Machine Learning. This unique combination is rare globally, providing our students with unparalleled opportunities. Our faculty actively contributes to and benefits from this thriving environment, e.g., with several professors being members of the Machine Learning Cluster of Excellence

If you're passionate about Machine Learning, AI, Data Science, and their applications in business and economics - come study with us!

Key Facts

4 Semester Program

Courses start in October

120 ECTS Credits

incl. Master Thesis (30 ECTS credits)

English and German

Course Language

The School of Business and Economics is a member of the AACSB Business Education Alliance

What do our students say?

"The program was the ideal choice for me, as it maintains a scientific basis while providing valuable data science skills" – Alumnus Finn Höner, PhD Candidate @ Erasmus University Rotterdam

"The program provides hands-on learning in scientific analysis within a collaborative environment, building practical data science skills for diverse business domains." - Alumna Maren Baumgärtner, Junior Data Analyst @ Marc Cain

"With a broad range of offered electives at different departments, the program can be perfectly tailored to your own interests." - Alumnus Tim-Moritz Bündert, AI Engineer @ Lufthansa & PhD student @ KIT

Picture of Jiazhen Li standing in front of the University

"The program stands at the intersection of theory and practice, offering a dynamic curriculum that has prepared me for the complexities of the data science industry." - Student Jiazhen Li, B.Sc. Int. Economics (Uni Tü)

"The learnings I gathered in Tübingen fostered my data-driven mindset and support me in effectively identifying corporate areas in which the involvement of data optimizes operational processes and enables strategic decision-making through insightful analyses." Alumnus Max Kneißler, Robert Bosch GmbH

Areas of Specialization

Econometrics
Business and Economics
Data Science Techniques, e.g.:
- Algorithms
- Big Data Computing
- Database Systems
- Data Science Project Management
- Basics of Machine Learning
- Causal / Probabilistic / Statistical Machine Learning
- Machine Learning Applications in Business and Economics
- Deep Learning
- Practical Deep Learning for Language Processing
- Practical Deep Learning from Visual Data

Curriculum

Modules / Areas	ECTS credits
Core Studies	27
Specialization Studies	12-24	30
Elective Studies	0-18	30
Data Science Project	12
Advanced Topics	9
Master Thesis	30

Ph.D. Track

Graduates will also find themselves well-positioned to pursue a Ph.D. subsequent to this M.Sc. program. For this purpose, students may study this M.Sc. program on a Ph.D. track, putting themselves on a fast track to a doctoral degree.

Module Handbook

For more detailed information about the modules, please see the Module Handbook.

Application

Deadline:

Application for all Master Programs is possible from March 1st until May 15th
(M.Sc. Economics: Until July 15th for international / September 15th for EU applicants, May 1st for Double Degree with Nottingham)

Application Portal

Bachelor Degree Requirements

Bachelor Degree Certificate in Business Administration, Economics or related fields with a final grade of at least 2.5 or better according to the German grading system. (The final grades of international applicants will be converted into the German grading system and therefore also be subject to this rule).

A certificate stating that the applicant has successfully completed a first university degree or a certificate (or equivalent documents) providing evidence of the successful completion of at least the year prior to his/her final examination in the equivalent studies.
Degree should preferably amount to 180 ECTS.

Complete Transcript of Records with a final grade or calculated grade average.

The transcript should prove the applicant has solid intermediate knowledge in

Statistics / Mathematics / Econometrics
Business Administration
Economics

Further, applicants must demonstrate their 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), in this case, applicants must provide detailed descriptions of the relevant courses, 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), e.g. certificates of online learning platforms that offer programming for Data Science courses.
In all cases, it is important that applicants provide clear documentation of their skills that allows the selection committee to make an informed assessment.

Transcripts of Records containing generic module titles (such as Business Administration I, II and III) should be accompanied by detailed module descriptions.

CV

CV in tabular format in English or German

Letter of Motivation

Please provide us with a letter of motivation explaining your reasons for applying for this degree and outlining your qualifications for it. Kindly limit yourself to one page, the letter may be composed either in English or in German.

Language Requirements

Proof of English Language Qualification

TOEFL ibt: 79 or
IELTS: 6.5 (overall band) or
Cambridge: CAE, CPE or BEC Higher or
German Abitur including at least 6 (G8) or 7 (G9) years of English or
Officially recognized higher education degree (e.g. Bachelor degree) entirely taught in English (English as the language of instruction) or
Transcript of Studies proving at least 30 ECTS-Credits were obtained in English-taught modules.

Please note that for the latter two options you must provide a medium of instruction certificate unless the language of instruction is definitively stated on your transcript!

Proof of ability to study in German (only for international students):

Information of German Language Requirements can be found on the website of the Student Affairs Office.

Additional Documents

Further documents proving specific qualifications relevant to the desired course of study may be submitted. Examples of these additional documents are, among others, proof of additional foreign language skills, results of standardized tests specific to the fields of Business and Economics (such as GRE or GMAT) and certificates of participation in summer schools or research projects that are not documented in the applicant's academic transcript. Please note that neither a GMAT nor a GRE are a prerequisite for any of our M.Sc. programs but that they may serve as an indication that the applicant possesses a certain skill set.

Note: It is not compulsory to send reference letters. However, if you wish to hand in reference letters, you can do so voluntarily.

Recognition of International Degrees

Please note that we as the academic advisory team are not in a position to provide accurate information regarding the recognition of international degrees in Germany. These matters are handled by our central Student Affairs Office (Advising and Admission of International Students) who can provide information about the recognition of specific degrees as well as grade conversion.

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Admission

Incoming applications will be reviewed by the admission committee to determine whether they meet the entry requirements and then ranked according to the grades the applicants obtained in ther undergraduate studies and other criteria.

Timeline Admission Process

March 1

application portal opens

May 15

application deadline

mid-June

interviews

June

offer letters are sent out by the end of June

October

start of the M.Sc. program

Interviews
After the admission committee has reviewed the applications they will invite the best candidates to take part in the next stage of the admission process, the interviews. Invitations will be sent out via email at least three days before the interview and will state the day and the time of the interview. Please make sure that you regularly check your emails. Interviews are conducted via Zoom. Admitted candidates will receive an admission letter 1-3 weeks after the interview. Students who receive an offer have only a limited period of time to accept the offer and matriculate at the University of Tübingen before the offer becomes invalid and the spot will be offered to the next candidate on the list.

Student Fees
The program is free of tuition fees for all EU residents, students are only obliged to pay a small administrational fee and a contribution to the student union to matriculate.

The state of Baden-Württemberg has introduced fees for international non-EU students and second-degree students in recent years. For background information and for fee exemption options, please refer to the following link:

Tuition Fees

Further Questions?

For further questions, please contact:

Academic Advisory Service

Want to talk in person? Make an appointment
Nauklerstraße 47 | 72074 Tübingen
+49 7071 29-76415
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Program Coordinator
Jun.-Prof. Dr. Michael Knaus
Prof. Dr. Stefan Mayer