AI Campus Original
AutoML - Automated Machine Learning
Spring 2021
14 weeks à 8 hours


The digital learning format "Automated Machine Learning" is intended to support future developers in the field of machine learning to make important design decisions automatically based on predefined data sets in order to achieve the best possible results in a short time when developing ML applications. The course, which is based on an offline event, is designed in such a way that it can be offered by universities in blended learning format with face-to-face and online phases or can be taken as part of a MOOC in self-study. 

Which topics will be covered?

  • Hyperparameter Optimization  

  • Neural Architecture Search  

  • Meta & Transfer-Learning 

What will I achieve?

By the end of the course, you‘ll be able to...

  • identify possible design decisions and procedures in the application of ML. 

  • implement the automatic optimization of design decisions.

  • evaluate the design decisions made.

Which prerequisites do I need to fulfill?

  • Basics in Machine Learning (ML) and Deep Learning (DL) 

  • First experiences in the application of ML & DL  

  • Python programming language  

  • Optional: Basics of Reinforcement Learning 

Who is offering this course?

Prof. Dr. Marius Lindauer
Prof. Dr. Marius Lindauer
Leibniz Universität Hannover
Bernd Bischl neu
Prof. Dr. Bernd Bischl
Ludwig-Maximilians-Universität München
Prof. Dr. Frank Hutter
Prof. Dr. Frank Hutter
Universität Freiburg
Prof. Dr. Lars Kotthoff
University of Wyoming
Prof. Dr. Joaquin Vanschoren
TU Eindhoven
Dr. Janek Thomas
Fraunhofer IIS

What else do I need to know?

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