Master of Science in Data Engineering and Analytics
Technical University of Munich
Duration
2 years
Intake
Summer, Winter.
Degree
Master’s
Program Overview
The Master of Science in Data Engineering and Analytics at the Technical University of Munich (TUM) equips students with advanced skills for handling complex, large-scale data. The program combines core topics in data engineering, including database technologies, big data systems, and scalable data processing, with analytical methods such as machine learning, statistical modeling, and data mining. Students develop the ability to extract valuable insights from diverse data sources and implement efficient data pipelines.
The interdisciplinary curriculum allows students to choose electives in areas such as mobility, health, or finance. Practical training, seminars, and a research-oriented Master’s thesis ensure strong technical expertise and real-world application. Graduates are highly qualified for careers as data scientists, engineers, or analysts in industries such as IT, finance, and healthcare, or for pursuing Ph.D. research in the rapidly growing field of data science. The program is taught in English.
Key Information
University
Technical University of Munich
Campus
München, Germany
Total Credits
120 ECTS
Study Mode
Full-time
Loan Availability
No
Program Details
Duration
Tuition Fee:
Format
Attendance:
Study Gap:
Fees & Funding:
Course Structure
Semester 1 (~30 ECTS)
Required Modules (31 ECTS total across semesters):
Foundations in Data Engineering (IN2326)—Winter start
Foundations in Data Analysis (MA4800)—Summer start
Advanced Seminar Course (IN2107)
Advanced Practical Course (IN2106)
Begin elective work in the following categories:
Data Engineering
Data Analytics
Data Analysis
Semester 2 (~30 ECTS)
Continue required seminar and practical courses (if not already completed)
Continue elective modules—must complete at least one module in each category:
Data Engineering, Data Analytics, Data Analysis
Pick further electives to satisfy distribution rules
Semester 3 (~30 ECTS)
Continue elective coursework across the three core areas
Ensure completion of:
≥15 ECTS in each of Data Engineering, Data Analytics, and Data Analysis
≥25 ECTS from Advanced Topics in Data Engineering and Special Topics in Analytics (choose at least one “Research Work under Guidance” or “Application Project”)
webarchiv.typo3.tum.de
Semester 4 (30 ECTS)
Full focus on Master’s Thesis (30 ECTS, ~6 months)
Entry Requirement
Academic
Language
IELTS - 6.5
TOEFL - 88
How To Apply
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