Technical University of Munich

Overview

The Master of Science (M.Sc.) in Data Engineering and Analytics at the Technical University of Munich (TUM) is designed to equip students with the skills necessary to create data platforms and derive insights from extensive datasets. The program integrates advanced topics in distributed systems, high-performance computing, and analytics to develop practical, data-driven solutions.

• Degree: Master of Science (M.Sc.)
• Programme Title: Data Engineering and Analytics
• Duration: 24 months (4 semesters, full-time)
• Credits: Typically 120 ECTS
• Delivery: On-campus
• Language of Instruction: English
• Location: Munich, Germany

What You'll Study

The curriculum is structured over four semesters and includes core courses in data engineering complemented by advanced analytics modules. While course offerings may vary, the program typically encompasses the following areas:

• Data Engineering & Systems Foundations: Focus on database systems, cloud data processing, and modern architectures for efficient data storage and retrieval.
• Distributed & High-Performance Computing: Study of distributed databases, distributed systems, parallel programming, and concepts in high-performance computing.
• Analytics & Applied Data Science: In-depth exploration of advanced analytics, including machine learning and business analytics for practical applications.
• Software & Implementation Skills: Emphasis on application and implementation of database systems along with programming-oriented modules for developing data services.

Typical Course Themes:

• Cloud-Based Data Processing
• Database Systems on Modern CPU Architectures
• Application and Implementation of Database Systems
• Advanced Concepts of Distributed Databases
• Programming Database Web Applications
• High Performance Computing – Programming Paradigms and Scalability
• Parallel Programming
• Distributed Systems

Final Thesis: The program culminates in a master's thesis, with specific requirements and timelines established by TUM for each intake.

Entry Requirements

While there are no specific GRE, GMAT, or GPA cut-offs publicly available for this program, admission is generally contingent on your previous academic background and the relevance of your coursework to the fields of data engineering and analytics.

Career Prospects

Graduates of the M.Sc. in Data Engineering and Analytics are well-prepared for a variety of careers in the tech industry. Potential roles include data engineer, data analyst, business intelligence developer, and cloud solutions architect, among others. The skills acquired during the program enable graduates to effectively contribute to data-driven organizations and tackle complex data challenges in diverse sectors.