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Heidelberg University
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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. ​

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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 2024

MSc Mathematics of Machine Learning and Data Science

Selected Colloquia

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Selected Lectures

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Computational Statistics and Data Analysis
Tristan Bereau
Dynamical systems theory in machine learning & data science
Daniel Durstewitz
Einführung ins Maschinelle Lernen
Dmitry Kobak
Generative Neural Networks for the Sciences
Ullrich Köthe
Machine Learning and Physics
Jan Martin Pawlowski, Tilman Plehn
Computer Vision: 3D Reconstruction
Carsten Rother
Introduction to GPU Accelerated Computing
Rainer Spurzem

Selected Seminars

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Scientific Machine Learning
Tobias Buck
Transformers, Large Language Models and their use in Physics
Dmitry Kobak
Risk management, Fairness and Transparency for AI
Jan Korbel, Fruzsina Molnár-Gábor 
Journal Club Advanced Machine Learning
Peter Lippmann
Machine Learning @ LHC
Tilman Plehn
Jounal Club Physics and ML
Tilman Plehn
Computer Vision Astrophysics and Cosmology
Caroline Heneka
Computer Vision
Bogdan Savchynskyy
Probabilistic Models and Machine Learning
Christoph Schnörr

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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