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263-5225-00L 2 Credits MSC , WBZ D-ITET , D-INFK , D-MATH
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Advanced Topics in Machine Learning and Data Science

Lecturers & Examiners: Prof. Dr. Fernando Perez Cruz, Dr. Ekaterina Krymova, Dr. Luis Salamanca Miño
The deadline for deregistering expires at the end of the fourth week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
VVZ CR n/a

Last Updated: 2026-02-05 16:38:51

Abstract

In this seminar, recent papers of the machine learning and data science literature are presented and discussed. Possible topics cover statistical models, machine learning algorithms and its applications.

Objective

The seminar “Advanced Topics in Machine Learning and Data Science” familiarizes students with recent developments in machine learning and data science. Recently published articles, as well as influential papers, have to be presented and critically reviewed. The students will learn how to structure a scientific presentation, which covers the motivation, key ideas and main results of a scientific paper. An important goal of the seminar presentation is to summarize the essential ideas of the paper in sufficient depth for the audience to be able to follow its main conclusion, especially why the article is (or is not) worth attention. The presentation style will play an important role and should reach the level of professional scientific presentations.

Content

The seminar will cover a number of recent papers which have emerged as important contributions to the machine learning and data science literatures. The topics will vary from year to year but they are centered on methodological issues in machine learning and its application, not only to text or images, but other scientific domains like medicine, climate or physics.

Resources

Literature

The papers will be presented in the first session of the seminar.

Learning Materials (Links)

General Information

Language
English
Levels
MSC , WBZ
Frequency
Yearly recurring

Examination

Type
graded semester performance

Registration & Places

Max Places
20
Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
seminar Advanced Topics in Machine Learning and Data Science
  • Wed 16:15-18:00 (LFW E 13)
2 h weekly

Offered In