Numerical Methods for Data Science

The course "Numerical Methods for Data Science" is a self-study course of type 2+1+1 SWS and takes place in summerterm 2021. There is a 2-hour lecture and a 2-hour exercise class every week.

  • Please contact Laura Burr if there are any questions about the lecture or exercise class. 


  • Due to the special circumstances this course will be a self-study course with online support by the lectures.
  • Both, the lecture notes and the exercise sheets are available on Moodle.
  • The first material will be provided on Monday, 19th of April. 


  • Learning
  • Least-Squares regression: SVD
  • Clustering and Classification
  • Machine learning, neural networks and others
  • Automatic differentiation
  • Probabilistic methods

Exercise Class

General Information
  • All informations about the exercise class can be found on Moodle.

Exam Requirement

  • 50% of the theory points as well as 50% of the programming points must be edited.