21. September



Helmholtz Virtual ML Summer School 2020

powered by Helmholtz Information & Data Science Academy (HIDA)
in cooperation with Helmholtz Artificial Intelligence Cooperation Unit (Helmholtz AI), Munich School for Data Science (MUDS), Ludwig-Maximilians-Universität München (LMU) and Munich Center for Machine Learning (MCML)


Core program of the Virtual ML Summer School 2020 is an introductory course to fundamental techniques and concepts of supervised Machine Learning, which has become a central part of modern data analysis.
In particular non-linear and non-parametric methods have been used successfully in uncovering complex patterns and relationships by computer scientists and statisticians.


Sep 21   ML Basics + Supervised regression
Sep 22   Supervised regression

Sep 23   HIDA virtual career day

Sep 24   Supervised Classification
Sep 25   Supervised Classification + mlr3 keynote

Sep 28   Evaluation
Sep 29   Trees + Random Forests
Sep 30   Trees + Random Forests
Oct  01   Tuning
Oct  02   Practical Advice

The focus of the course is to give a basic understanding of the different algorithms, models and concepts while explaining the necessary mathematical foundation.

Participants will acquire theoretical as well as practical competencies regarding some fundamental models of learning from data. Also participants will be enabled to conduct a data analysis project, including understanding and interpreting the data, in order to critically judge the advantages and disadvantages of the different methods.


The course is targeted at ML beginners with a basic, university level, education in maths and statistics:

  • Basic linear algebra: vectors, matrices, determinants
  • Simple calculus: derivatives, integrals, gradients
  • Some probability theory: probability, random variables, distributions
  • Basic statistics knowledge: descriptive statistics, estimators.
    (Linear) modelling from a statistics perspective will help, but is not required.
  • Working knowledge of R


Prof. Dr. Bernd Bischl (LMU Munich, MCML); Tobias Pielok (LMU Munich); Dr. Heidi Seibold (HMGU, LMU Munich, Bielefeld University); tba


The registration deadline is 31.07.2020. If the demand is too high, we will create a waiting list. You will be informed after the submission deadline whether a place is available or whether you are on the waiting list.
Helmholtz doctoral researchers have priority. We provide a limited number of places for external applicants. No fees!

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MUDS, Helmholtz AI and HIDA are part of the Helmholtz Incubator Information & Data Science.