Master of Science

Data & Society

Technical University of Munich

München, GermanyData Science & AI

APS Requiredfull-time

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Degree

Master of Science

Language

English

Tuition

€6,000/sem

Duration

4 semesters

Programme Overview

Interdisciplinary master's programme for STEM graduates who want to understand and shape data-driven technologies in relation to human behaviour, social needs, regulation, and sustainable development.

Admission Requirements

Academic requirements: Motivation Letter: Submit a written motivation letter of up to 150 words explaining why you have chosen the Data & Society programme at TUM. Highlight your fit for the programme and provide examples, such as relevant internships, study-abroad experiences, or any professional or academic training demonstrating your qualifications for this field. Interview: Selected applicants will be invited to an interview. The interview will last between 20 and 30 minutes in English. It will cover your motivation for applying, your academic background in MINT (STEM) fields, and your ability to work scientifically and methodically.
Minimum GPA: No fixed minimum GPA is published; admission is based on the aptitude assessment and interview.
English requirements: English is the required language of instruction and proof of English is required according to TUM's recognized language-proof rules.
Accepted bachelor fields: A completed STEM bachelor's degree is required.
APS Certificate: Yes

Costs & Funding

Tuition fee: 6,000 EUR per semester for international students from third countries; otherwise none.
Semester contribution: 97.00 EUR student union fee per semester at the Munich campus.
ECTS credits: 120
Funding info: Tuition: 6,000 EUR per semester for international students from third countries; otherwise none. Semester contribution: 97.00 EUR student union fee per semester at the Munich campus.

Career Outcomes

Graduates are competent engineers and scientists with specific expertise in evaluating modern technologies' opportunities, risks, and regulations. They are able to reflect on, analyse, and assess the economic, ecological, social, political, and ethical dimensions of data-based technologies and manage their use in line with specific requirements. As a result, they are just as well qualified to take on leadership roles in technology-driven companies or public administration as they are to continue their academic work within the framework of a doctoral dissertation.

Specialisations

Data PerspectivesHuman & SocietyRegulatorySustainable Development

Typical job roles

Leadership roles in technology-driven companiesPublic administration rolesAcademic researcher (doctoral dissertation)

Target industries

Technology-driven companiesPublic administrationResearch institutions