138.129 Machine Learning and Data Compression in Physics
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, PR, 8.0h, 10.0EC


  • Semester hours: 8.0
  • Credits: 10.0
  • Type: PR Project
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to comprehend the materials presented in the lecture and to draw conclusions from them, as well as to actively communicate the contents presented during the lecture.

Subject of course

Machine learning has become an important tool in the analysis of data and as prognosis tool in science and engineering. This method continues to be an active field of research, but its knowledge also provides students with an excellent perspective for jobs in industry. The project work is concerned with the application of machine learning concepts in physics and engineering, as well as with the development of new tools, e.g., for the compression of data or in optimization problems, pattern recognition, and the prediction of observables. The project is ideally suited to deepen the knowledge aquired in the lecture 138.128 "Machine Learning in Physics".

Teaching methods

Interactive course

Mode of examination




Examination modalities


Course registration

Not necessary


Study CodeObligationSemesterPrecon.Info
033 261 Technical Physics Mandatory elective
066 460 Physical Energy and Measurement Engineering Mandatory elective
066 461 Technical Physics Mandatory elective


No lecture notes are available.

Previous knowledge

We recommend taking the course 138.128 Machine Learning in Physics




if required in English