Handling and analyzing very large amounts of data is an urgent problem in many areas of science and industry and requires novel approaches and techniques. The trend towards "Big Data" is caused by a host of developments: Firstly, the creation and storage of large data sets becomes feasible and economically viable, for example due to price decreases in storage space, sensors, smart devices, social networks and many more.
Secondly, technical advances for example in multi-core systems and cloud computing make it possible to examine data sets at large scale. And thirdly, such amounts of data do not only origin in the "classical" domains like business data, but now are created in many areas of life. Consider vehicles, that create sensor data and share information via intelligent networking, or consider data that is created by intelligent energy grids.
Which professional opportunities can I take up with this qualification?
- The master’s programs “Mathematics in Data Science” and “Data Engineering and Analytics” offer access to many career opportunities including: research, consulting, IT security, systems design, and data science in industry.
- The respective departments offer Ph.D. positions that are the pathway to a career in research. Typical job profiles in industry include data analysts and data engineers. Data engineers master very large databases and distributed information systems and are responsible for IT security and applied data analytics for structuring data.
- Data analysts filter and extract information from large data sets based on statistical and mathematical methods and tailor them towards informed strategic decisions
- The curriculum comprises mandatory courses on Data Analysis and Data Engineering. Advanced lectures are offered in these area of studies: Data Engineering contains lectures about distributes systems, distributed databases, query optimization, database systems on modern CPU architectures and high performance computing.
- Data Engineering and Analytics offers lectures about machine learning, business analytics, computer vision and scientific visualization. Data Analysis is concerned with topics that require solid mathematical foundations: Fundamentals of Convex Optimization, Computational Statistics and more.
- 24 months
Start dates & application deadlines
- Apply before
DisciplinesIndustrial & Systems Engineering Data Science & Big Data View 36 other Masters in Data Science & Big Data in Germany
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InternationalFreeTuition FeeBased on the original amount of 0 EUR per semester and a duration of 24 months.
EU/EEAFreeTuition FeeBased on the original amount of 0 EUR per semester and a duration of 24 months.
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