|
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 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 | |