The field of "Data Science" is located at the intersection of mathematics, computer science, and statistics. Data Science is concerned with the analysis and extraction of knowledge from data as well as the techniques required to process large and often unstructured data sets.
In the bachelor's degree program "Applied Data Science", in-depth knowledge of data analysis is taught, building on the fundamentals of computer science and mathematics. Furthermore, students learn how to apply the learned methods for data analysis in an application subject they choose.
The domain of data analysis includes aspects of machine learning, statistics, pattern recognition, and the infrastructures needed for efficient analysis. Students can choose Digital Business Administration, Biology/Bioinformatics, Digital Humanities, Medical Informatics, Breeding Informatics, Physical Modeling and Data Analysis, and Computational Sustainability as application subjects.
The bachelor's degree program "Applied Data Science" requires a total of 180 credit points to be earned. The study program is divided into the areas of subject studies, professionalization and bachelor thesis. Detailed information on the structure of the study program, on application subjects and on modules can be found in the module directory under the link "Regulations" in the right column. Sample study plans can be found in the examination and study regulations.
- Fundamentals of computer science
- The mathematical foundations of Data Science
- Fundamentals of Data Science
- Elective area »Data Science«, e.g. Advanced Machine Learning
- Elective area »Subject of application«, e.g. Digital Business Administration or Biology
- Practical courses / Advanced research training
- Key competencies, e.g. Programming or language courses
Data Scientists are currently in demand in almost all disciplines, both in research and in business. Possible employers can be found for example in marketing, banks, insurance companies, the IT sector, management consultancies, public research institutes , in the pharmaceutical sector (clinical trials), in the public health sector as well as in colleges and universities.
Given the proximity of the training to the application domains directly at the university, research departments dealing with data-driven research in the domains in question are prospective areas of work. In all of these domains, there is currently a lack of specialists in Germany.
Advanced knowledge in English is recommended.
See more at: Language requirements for international prospective students
The ability to work in a team is an important prerequisite for later professional life.
Specialized technical knowledge, especially in programming, is not a prerequisite for this programme.