IMPRS / Origins Data Science Block Course


The Origins Data Science Lab (ODSL) and the International Max Planck Research School on Elementary Particle Physics (IMPRS) is organizing a block course on "Introduction to Machine Learning" targeted towards PhD students in physics. Interested MSc students from LMU and TUM are welcome as well.

The courses will take place in person at the MPP building at  Forschungszentrum Garching. The lectures and tutorials will take place in person in the Alps room (A.1.01/03) which is the main auditorium located on the first floor of the MPP. After entering the building via its main entrance on the Boltzmannstrasse, please take the stairs to the right of the Heisenberg cafe to get to the first floor. When reaching the first floor, the main auditorium is directly on the right hand side and facing the Boltzmannstrasse.

Note that the automatic glass main entrance works only until 4:00 PM. Thus, for the sessions starting at 4:00 PM it will be recommended to enter the building already at 3:50 PM.

The two-week introductory block course (15.04.2023 - 25.04.2023) will cover the following topics:

  • First Week:
    • Linear models, supervised learning 
    • Machine Learning theory (bias / variance trade-off)
    • Classical clustering algorithms
    • Boosted Decision Trees
    • Intro to Neural Networks (universal approximation theorem, optimizers)
    • Automatic differentiation, deep learning frameworks (e.g, pytorch)
  • Second Week:
    • Convolutional Neural Networks (grid-based models)
    • Sequence-based models and Transformers
    • Geometric Deep Learning and Graph Neural Networks 
    • Deep Generative Models

Please Register for the Event using the Registration Link.

With lecturers:

  • Nicole Hartman,
  • Baran Hashemi,

Repository with Exercises: GitHub

Forms of credit: This semester there will be no official ECTS credits. We'll have time for tutorials with tutors available to help work through the solutions, but there is not a need to submit these tutorials for a course grade. Certificates of participation may be provided on request.

Zoom connection

Meeting ID: 634 3194 6615

Passcode: 443046



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  • Alena Khokhriakova
  • Alessandro Ratti
  • Ana Bacelj
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  • Jakob Linder
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