Germany
University of Tubingen

University of Tubingen

Tubingen, Germany

MSc in Data Science in Business and Economics

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Data Science & Big Data

Specialization

2 years

Duration

€3,000 overall

Tuition Fee

fall

Intake

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Eligibility Requirements Rankings Program Description Program Curriculum Scholarships

Eligibility Requirements for Tubingen MSc in Data Science in Business and Economics

English Requirements

IELTS 6
TOEFL IBT 80

General requirements

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).

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)

WUR

78th

Tubingen MSc in Data Science in Business and Economics Program Description

Key Features

The Data Science in Business and Economics program from University of Tübingen 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.

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.