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Faculty of mechanical engineering
Qualification Concept for Machine Learning in Industrial Production

Industrial Data Science (InDaS)

Industrial Data Science (InDaS) is a forward-looking qualification concept for the further education and training of young academics and industry specialists. For this purpose, we teach the contents from a network of institutes and chairs, whereby we strive for a high degree of topicality as well as practical testing of the taught contents: Through close cooperation with our industrial partners, small student groups from the disciplines of computer science, statistics and engineering can work on and solve real-life application cases.

Contents of the InDaS course

The course "Industrial Data Science" is the result of a research and development project funded by the Federal Ministry of Education and Research as part of the programme "ICT 2020 - Research for Innovation" and supervised by the project management organisation Deutsches Luft- und Raumfahrtzentrum e.V. (DLR). During this research project, we four chairs merged into a joint teaching consortium. In doing so, we combine the three disciplines of computer science, statistics and engineering and teach the students in a closely coordinated manner over two semesters. Due to the high heterogeneity of our student body, we constantly strive to update and adapt the course content to meet the different requirements.

In order to complete the entire course, students must pass two sub-modules: The theory phase and the practical phase. While in the theory phase we teach basic contents through lectures and exercises, in the practical phase we supervise small student groups in the processing of real application cases, which are provided to us by our industrial partners. The Institute of Production Systems (IPS) is responsible for coordinating both the course and the research project.


The lecture and exercise dates for InDaS 1 are based on the usual guidelines of the TU Dortmund University. The dates given for InDaS 2 correspond to attendance dates on which the acquired content is presented by the student small groups. There are still consultation dates within the practical phase, but these are not obligatory.


Industrial Data Science is principally aimed at all students of the faculties of Mechanical Engineering, Statistics and Computer Science. Prerequisites for participation are a completed Bachelor's degree and a high interest in the field of data analysis. In addition, basic programming skills should be available.


If you cannot register for the exam via BOSS, please contact the relevant supervisor in your department:

Mechanical Engineering: Contact
Computer Science: Contact
Statistics: Contact

As a member of the Faculty of Mechanical Engineering, InDaS 1 must have been passed before InDaS 2 can be taken.


Both specified exam dates are to be considered equivalent. However, in case of failure of the first date, another attempt can be made in the following date.