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401-2684-00L
5
Credits
BSC
D-MATH
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Mathematics of Signals, Networks, and Learning
Last Updated: 2026-02-05 16:22:17
Abstract
Introductory course to Mathematical aspects of Machine Learning, including Supervised Learning, Unsupervised Learning, Sparsity, and Online Learning.
Objective
Introduction to Mathematical aspects of Machine Learning.
Content
Mathematical aspects of Supervised Learning, Unsupervised Learning, Sparsity, and Online Learning. This course is a Mathematical course, with Theorems and Proofs.
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 150 minutes
- Aids
- None
A bonus of up to 0.25 grade points can be achieved by the submission of a small number of homework solutions (more details to be announced in the course). (This is non-mandatory, and the maximum grade of 6 in the course unit can still be achieved by simply taking the final examination.)
Registration & Places
- Max Places
- 100
Priority: Registration for the course unit is until 30.01.2023 only possible for the primary target group
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Mathematics of Signals, Networks, and Learning (formerly: Mathematics of Machine Learning) |
|
2 h weekly |
| exercise |
Mathematics of Signals, Networks, and Learning (formerly: Mathematics of Machine Learning)
Groups are selected in myStudies.
|
|
1 h weekly |