Overview
Overview
Data science is a highly relevant and interdisciplinary field of research and work which links computer science, mathematics and domain knowledge. The analysis of large pools of data, e.g. using methods of artificial intelligence and machine learning for the extraction of useful information has become an integral part of today's society and a number of career fields. If a stronger focus is applied to computer science and domain knowledge, we find ourselves in the field of data analytics.
The Master's degree program "Data Analytics" is aimed at Bachelor's students who wish to expand the domain knowledge they acquired in their Bachelor's degree, which is not related to computer science, with skills in the field of data science, i.e. mathematics and computer science, and thus become capable of in-depth scientific work in the field of data analytics. This programme is accessible to students with a Bachelor’s in the following fields:
- Economics
- Natural Sciences
- Life Sciences
- Engineering
- Agricultural Sciences
- Environmental Sciences
- Nutritional Sciences
However, students with other Bachelor’s degrees (e.g. Humanities and Social Sciences) may also be permitted to enroll following an inspection by the board of examination.
This course of study expands upon the students‘ domain knowledge gained during the bachelor’s programme. During the first year of studies, the programme primarily focuses on methods of modern data analysis, including basic concepts of computer science, data base programming, aspects of information and data management, basic methods of artificial intelligence, as well as the fundamentals of data analysis and visualisation. The second year of studies covers a project phase and the Master Thesis, which combines domain knowledge with these methods of data analysis.
"Data Analytics" is offered as a hybrid degree programme, allowing students to study in person, entirely digital or a combination of the two. This also applies to projects and the Master’s Thesis. Students may switch at any time, including during the lecture period. Furthermore, the content of lectures, tutorials and seminars is made available digitally and asynchronously.