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Universität Heidelberg
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Learning about ML

Heidelberg University is a stimulating and diverse environment allowing you to take select courses in machine learning, or even study for a full degree. ​

Young Researchers Working at the Computer

Study Machine Learning

Heidelberg University offers a number of complementary MSc programs where you can both study foundations and learn about the latest trends in machine learning. Our degrees are tailored to equip you with the fundamental knowledge that is essential to accede to leading positions in academia, and challenging jobs in industry.

Starting in Fall 2023

MSc Mathematics of Machine Learning and Data Science

Selected Colloquia

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Selected Lectures

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Dynamical Systems Theory in Machine Learning & Data Science
Daniel Durstewitz
 
Introduction to High Performance Computing
Holger Fröning
 
Machine Learning & Neuronale Netze in der Medizin: Grundlagen und Risiken
Niels Halama
Machine Learning and Physics
Fred Hamprecht
 
Tutorial on Statistical Methods for Reproducible Machine Learning
Stefan Riezler
 
Computer Vision: 3D Reconstruction
Carsten Rother
 
Optimization for Machine Learning
Bogdan Savchynskyy
 
Introduction to Neural ODEs and Assignment Flows for Machine Learning
Christoph Schnörr
 
Machine Learning in Practice
Arne Jonas Warnke
 

Selected Seminars

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An Introduction to Machine Learning
Lars Feuerbach
Machine Learning for the Biomolecular World
Frauke Gräter & Rebecca Wade
 

Resilient Machine Learning

Holger Fröning
Mensch und Automat
Ullrich Köthe
 
Journal Club Advanced Machine Learning
Peter Lippmann
 

Machine Learning Talks on Campus

Machine Learning Talks on Campus is an information service about talks, workshops and other events in the local community.

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