Module Number

ML-4510
Module Title

Practical Machine Learning
Lecture Type(s)

Practical Course
ECTS 6
Work load
- Contact time
- Self study
Workload:
180 h
Class time:
60 h / 4 SWS
Self study:
120 h
Duration 1 Semester
Frequency Irregular
Language of instruction English
Type of Exam

Oral presentation, written report, lab journal

Content

The practical course consists of finishing assigned tasks in small teams, autonomously or under supervision. Study and exam performance are usually evaluated based on active participation, a presentation of results and in written
reports.

In the summer term 2026, the course "Build your own StudyOS with Modern Agentic Systems" (Prof. Gehler) will be offered (see: https://alma.uni-tuebingen.de:443/alma/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=67159&periodId=229&navigationPosition=studiesOffered,searchCourses)

Objectives

Students will gain practical experience in designing and programming methods / software /tools for ML. They will be able to use libraries and frameworks, and will acquire knowledge or extend their knowledge of various programming languages. By working together in groups, students obtain teamwork and collaboration skills, and they will learn about project organization and presentation techniques. Students will know about the strengths and weaknesses and about the limitations of various methods for evaluating complex and high-dimensional data, and will be able to describe and evaluate these methods.

Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Practical Course
P
o
4
6.0
tp, op
g
100
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Alle Dozenten
Literature

-

Last offered unknown
Planned for currently not planned
Assigned Study Areas INFO-INFO, MEDI-APPL, MEDI-INFO, ML-CS, ML-DIV