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Industrial Data Science

Course Structure


Prof. Dr. Jochen Deuse

Jun.-Prof. Dr. Thomas Liebig

Prof. Dr. Markus Pauly

Prof. Dr. Jens Teubner



Lecture:  Friday 08:15-09:45 am at EF50, HS 1
Exercises: Friday 10:15-11:45 am at SRG1, H.001


Language and Format

  • The course will be held in English.
  • Both lecture and exercises will be taught offline.


Suitable modules

MS 6,7; MD Applications

(5 ECTS points)



Registration is via Moodle.

Course: Industrial Data Science 1 WS 22/23, LSF, 042537


Course outline

The course covers  the basics of data mining and data management as well as their industrial applications.  Specifically, the lectures will embrace the following topics, among others:

  •     Data and data analysis in industrial environments
  •     Data Management
  •     Univariate statistics, correlation and regression, feature selection
  •     Decision trees and random Forests
  •     Cluster analysis and topic modeling
  •     Model selection
  •     SVMs and neuronal networks


Basic knowledge in math and programming

Follow-up course

In the summer term 2022, a course Industrial Data Science 2 will be offered, in which the learned, theoretical material can be practically applied to real industrial use cases. This course can be credited for master of data science students as MD Applications (5 ECTS)

Further information about the course concept can be found here.