Data Science Master
The international English four semester Data Science Master with the degree Master of Science (M.Sc.) has started October 2017/2018 at Beuth University of Technology (App. Sc.) and will run annualy start each winter-semester! The national and international application pages should open from 1st May to 15th of June for the next 22+ seats. Most of the student questions are answered in the FAQ!
All accepted students are informed in our system! Please read the FAQ #23 for more information! Because external providers block us, the study administration cannot reply to emails from outlook, live and hotmail or send rejections! Contact the head of this master for more information.
Goal of the Master
The master will qualify students to analyse big data efficiently and to create systems/solutions for AI / Machine Learning. Therefore they will be all set for future industrial demands. The focus areas of this Data Science Master are "Urban Technologies" and "Intelligent Machines" and is explicitly interdisciplinary constructed.
After the basic knowledge of Data Science (as Computer Science and Statistics) we will teach a wide range of Machine Learning methods and AI practicies. Furthermore the most important tools, practices - as data preparation and big data analytics - will be taught and implemented practically. Additionally, we do have the possibility to work on an innovative idea right from the beginning to the end to create a start-up or together with leading companies in Berlin.
Furthermore, questions of ethics, responsibility and data protection as well as economic knowledge and analysis are integrated in order to convey an important change of perspective. The thesis on the Master of Science will be embedded in current research projects and industrial cooperation.
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NEWS
Exciting News! A team of four BHT Data Science students – Jai Kushwaha, Farel Arden, Shadi Farzankia, and Nahid Taherkhani – has won the 3rd prize at the prestigious HERE Hackathon 2025.
Beyond the competition, they embraced the opportunity to connect with fellow participants and mentors, finding the experience highly rewarding and the datasets provided particularly interesting. On behalf of BHT and all Data Science Professors, congratulations on this outstanding accomplishment!
Supported by
- Berliner Qualitäts- und Innovationsoffensive (QIO 2016 – 2020) Förderlinie III b III. b) Hochschulübergreifende Maßnahmen für Innovation
- Einstein Centre / Digital Future Berlin
- BMBF Berlin Big Data Center BBDC
- BMWi Smart Service Welt - MACCS
- BMWi Smart Data - Smart Data Web und ExCELL
- EU H2020 - FashionBrain
