Lecture: 2.01.5402 Trustworthy Machine Learning - Details

Lecture: 2.01.5402 Trustworthy Machine Learning - Details

General information

Course name Lecture: 2.01.5402 Trustworthy Machine Learning
Subtitle inf5402
Course number 2.01.5402
Semester SoSe2025
Current number of participants 22
expected number of participants 25
Home institute Department of Computing Science
Associated institutions Department of Health Services Research, Department of Medical Physics and Accoustics, Institute of Physics
Courses type Lecture in category Teaching
First date Wednesday, 09.04.25, 12:00 - 14:00 o'clock V02 0-002
Type/Form V+Ü
Lehrsprache deutsch und englisch

Rooms and times

V02 0-002

  • Wednesday, 12:00 - 14:00, Weekly (from 09.04.25)
  • Thursday, 08:00 - 10:00, Weekly (from 10.04.25)

V03 S-206

  • Wednesday, 06.08.25, 09:00 - 12:00 o'clock

Comment/Description

Machine learning algorithms find its way into an increasing number of (safety-critical) application domains but their quality is rarely assessed in a systematic way. The focus of this module are quality criteria for machine learning algorithms, in particular of deep neural networks, ranging from performance evaluation over explainability/interpretability (XAI), robustness (adversarial robustness, robustness against input perturbations), uncertainty quantification, distribution shift, domain adaptation, fairness/bias to privacy. The methods are introduced theoretically in the lecture and implemented/applied practically in the exercises. Prerequisites are basic theoretical knowledge in machine learning, programming skills in Python and ideally practical knowledge in training neural networks.

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".
Erzeugt durch den Stud.IP-Support
The following rules apply for the admission:
  • Admission locked.