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Technical University of Munich Master of Science in Data Engineering and Analytics

The Technical University of Munich (TUM) is offering a two-year full-time Master's programme in Data Engineering and Analytics. This programme is taught entirely in English and will explore innovative solutions for handling and analysing very large amounts of data. Graduates of this programme will be able to design and plan industry-grade solutions in the area of Big Data and undertake research projects should they be interested in pursuing these.

Structure of the programme

The programme is divided into three areas of studies: Data Analysis, Data Engineering and Analytics, and Data Engineering. Under the Data Analysis area, students will learn the fundamentals of understanding and modelling data and the underlying relationships. Data Engineering consists of lectures about the construction of systems that perform efficient and scalable data processing. Finally, Data Engineering focuses on distributed systems, distributed databases, query optimisation, database systems on modern CPU architectures and high performance computing. The curriculum, including the modules for each area, can be consulted on the TUM website.

Requirements

Applicants must have a recognised undergraduate degree and must successfully complete the aptitude assessment procedure. This procedure allows the TUM to evaluate the applicant's individual talents and motivation for study. 

Training Offer Details

Target audience
Digital skills for ICT professionals and other digital experts.
Digital technology / specialisation
Digital skill level
Geographic scope - Country
Germany
Industry - field of education and training
Information and communication technologies not elsewhere classified
Target language
English
Geographical sphere
National initiative
Typology of training opportunties
Learning activity
educational programme
Assessment type
Training duration
Is this course free
No
Is the certificate / credential free
No
Effort
Full time
Credential offered
Qualification Award
Self-paced course
No