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401-2684-00L 5 Credits BSC D-MATH
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Mathematics of Signals, Networks, and Learning

Lecturers & Examiners: Prof. Dr. Afonso Sousa Bandeira
VVZ CR n/a

Last Updated: 2026-02-05 16:37:25

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 29.01.2024 only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture Mathematics of Signals, Networks, and Learning
  • Fri 14:15-16:00 (HG D 3.2)
2 h weekly
exercise Mathematics of Signals, Networks, and Learning
Groups are selected in myStudies.
  • Mon 12:15-13:00 (HG E 33.1)
  • Mon 12:15-13:00 (HG E 33.3)
  • Mon 12:15-13:00 (HG F 26.5)
  • Mon 12:15-13:00 (HG G 26.5)
1 h weekly

Offered In