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Robotics, Cognition, Intelligence (M.Sc.)

at TUM in Munich

At a glance

Language
Bilingual
Duration
4 sem 120 ECTS
Intake
Winter & summer
Tuition
€6,000 per semester; see fee notes
Semester fee
€97

● Closed for this intake All applicants · Winter semester The window usually repeats next cycle; the full deadline table below shows every route and date.

Interdisciplinary robotics and AI master - unique in Germany in drawing electives from informatics, mechanical engineering and electrical engineering - covering robotics principles, machine learning, embedded systems and human-robot interaction with substantial practical projects. ⚠ Language: TUM requires both German and English; lectures are offered in both, so this is not an English-only degree. Based at TUM's Garching research campus, approximately 15km north of Munich city centre, connected by U-Bahn (U6).

Admission requirements

Prior degree
B.Sc. in electrical or mechanical engineering, physics, computer science or a related field (embedded/systems engineering also considered)
Minimum grade
not confirmed
English
Sufficient English per TUM's accepted certificate list (GMAT above 600 or an English-medium prior degree also accepted)
German
German AND English both required: TUM states "You need sufficient German and English language skills if you wish to apply for this program." Lectures are offered in both languages, so this programme cannot be completed in English alone.
Also required
Eignungsverfahren (aptitude assessment) required as part of the application process. Applicants are ranked; meeting minimum requirements does not guarantee admission. Personal statement (max. two pages), CV and a scientific essay of about 1,000 words. GRE or Indian GATE mandatory for applicants with degrees from Bangladesh, China, India, Iran or Pakistan. uni-assist VPD (Vorprüfungsdokumentation) required for applicants with a non-German bachelor's degree; APS certificate required for applicants from China, India and Vietnam.

Deadlines & timeline

Deadlines differ by where your degree is from. Dates change every cycle, so always confirm on the official page before planning. Where no fixed calendar date exists or none is confirmed yet, the Details column explains each case.
Who Intake Deadline Details
All applicants Winter semester closed for this intake; next cycle usually repeats the same window Application window 1 February - 31 May annually via TUMonline. TUM strongly encourages non-EU applicants to apply by 15 March so there is time for visa processing; missing documents such as the uni-assist VPD can follow until the final deadline.
All applicants Summer semester Application window 1 October - 30 November annually via TUMonline.

Fees & funding

Tuition
€6,000 per semester
Semester contribution
€97
Semester ticket
not included

⚠ TUM charges tuition to non-EU/EEA students newly enrolling from WS 2024/25: €6,000/semester for this programme, on top of the €97/semester Studierendenwerk fee. EU/EEA citizens and holders of a German bachelor's degree or German Abitur pay no tuition; merit- and need-based fee waivers exist. No semester ticket is bundled - students subscribe separately to the discounted student Deutschlandticket. Verify at https://www.tum.de/en/studies/fees

Scholarships are listed per university: see TUM scholarships.

How to apply

uni-assist
required (the deadline table shows who this applies to)
Application portal
campus.tum.de
Official page
www.cit.tum.de

EU applicants and holders of German degrees usually apply directly via the university's Campusportal instead of uni-assist; the deadline table above says which route applies to you.

What students say

Via StudyCheck · 2024-2026: an aggregated rating, not our own assessment, paraphrased in our own words and never quoted.

4.6 /5

The highest-rated TUM programme in our set: 15 StudyCheck reviewers average 4.6/5. They describe demanding but rewarding content bridging robotics, AI and cognitive science, with valued interdisciplinary, research-adjacent projects and reliable hybrid teaching. Exams come up repeatedly as intense (some stress tolerance is advised), but the programme's strong reputation is seen as earned.

Liked

  • Demanding but rewarding blend of robotics, AI and cognitive science
  • Interdisciplinary, research-adjacent project work
  • Reliable digital and hybrid teaching infrastructure

Criticised

  • Exams described as intense; stress resistance advised

Where graduates go

No alumni outcome data found yet.

External resources

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