Nowadays many businesses produce and process huge amounts of data, for example in the manufacturing industry by deploying the industrial data space or the medical data space used by the health industry. Methods, processes and tools for data analysis and visualization are therefore becoming key ingredients in producing knowledge necessary and instrumental for decision processes. This lab course teaches methods and tools for analyzing and visualizing data sets. It conveys the technical foundation as well as gives ample opportunities for practicing data analysis and visualization on real-world data. Innovation of analysis is founded in method orchestration. At the beginning of the course, the key concepts of data analysis and visualization are taught by using Python as a free open-source software package. This part will focus on machine learning methods such as linear regression models and cluster analysis as well as on creating (interactive) visualization. In the second part, students combine these methods to answer increasingly more complex questions. The heart of this course consists of group specific applied projects, in which existing data sets are analyzed to answer questions from the operative environment. Please note that specific sessions (e.g. kick-off session, final examination) of this course take place on-site in Sankt Augustin at the Fraunhofer Institute for Applied Information Technology (Fraunhofer FIT).
Resulting data sets allow real-world questions to be answered in a full quantitative stance which used to be hard or even impossible to answer previously: has the internet had country-specific impacts on governance, has government spending on infrastructure had a tangible effect on private mobility and what decisions during a car’s development cycle turn out to be most profitable in the end?
Supplementary techniques, which can be covered offhand, include the visualization of maps and graphs, image analysis, combining multiple data sets and more.
All of these methods and techniques are practiced using applied real-world data sets.
Apart from acquiring the functional and technical foundations, students will experience the operative potential of data analysis and its application in analysis processes. In effect, this data science course is turning into a living lab.
| Type | Lab (advanced level) |
| Term | WS 2026 |
| Starting | 30.10.2026 at 10:00am |
| Mentor(s) |
Marc Kerstan |
| Assistant(s) |
Here is some additional information about the course:
- – Starting on Friday, 30 October 2026, our weekly sessions will take place from 10:00 a.m. to 2:00 p.m.
- – Our kick-off session will take place at b-it Bonn (Friedrich-Hirzebruch-Allee 6, 53115 Bonn), in Room 0.107.
- – The lab includes both online and in-person sessions, with approximately four in-person sessions taking place at b-it Bonn.
- – Attendance at all sessions is mandatory.