- Degree
- Master of Science in Data Analytics
- Course location
- Hildesheim
- Teaching language
- • English
- Languages
- English only
- Full-time / part-time
- • full-time
- Programme duration
- 4 semesters
- Beginning
- Winter and summer semester
- Application deadline
- Non-EU applicants: 30 June for the following winter semester
EU applicants: 31 August for the following winter semester
Non-EU applicants: 15 December for the following summer semester
EU applicants: 15 February for the following summer semester
- Tuition fees per semester in EUR
- None
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- The international Master’s programme in Data Analytics offers a comprehensive and forward-looking education in modern data science, combining rigorous training in state-of-the-art machine learning, big data technologies, and statistical analysis with application-oriented knowledge from selected domains.
Students gain a deep understanding of advanced analytical methods and acquire the practical skills needed to model and interpret complex systems. The programme prepares graduates to address real-world challenges across a variety of sectors, including business areas like marketing, finance, and logistics as well as scientific fields such as computer science and environmental studies.
Teaching is closely integrated with ongoing research and industry practice. The curriculum is developed and delivered by experienced faculty and domain experts, ensuring that students are exposed to both theoretical foundations and practical applications throughout their studies.
Course Highlights
Project: The project spans one academic year and is conducted under the supervision of a faculty member. Students independently explore advanced topics in machine learning, gaining hands-on research experience. Many student groups have presented their work at major conferences and even received awards for their contributions.
Application Modules: These modules allow students to explore how machine learning is applied in various domains such as natural language processing, business administration, psychology, and climate science. They provide valuable interdisciplinary insight into real-world applications of data analytics.
Methodological Specialisation: Students deepen their expertise through specialised courses in advanced machine learning topics. Offerings may include areas like computer vision, time series analysis, and other cutting-edge methods tailored to specific analytical challenges.