Communication Technologies 1
(Machine Learning)
Creditability:
- Informatics-master course: 4 SWS
- Electrical engineering - Telecommunications: 4 SWS
- Master Program Electrical Communication Engineering: 4 SWS (only if you started your study before 2024)
Kind of lecture:
Lecture and presentations
Language:
By arrangement
Target audience:
- Informatics - Technical informatics
- Electrical engineering - Telecommunications
- Master program electrical communication engineering (only if you started your study before 2024)
Topics:
The lecture contents i.a. following topics:
- Introduction to machine learning
- Data collection
- Nominal data
- Time series
- Introduction in how to write (composing) scientific papers
- Feature Selection
- Classification
- Bayesian networks
- Markov models
- Decision trees
- Neural Networks
- Clustering
Learning objectives:
- Development of new subject matters,
- Presentation of subject matters - both are very important skills for the industry
- Scientific working (papers) and publishing
- Content: overview of matrix detection
Examinations:
- Discourse and 5-sided paper
- No written exam
Start of the lecture
Thursday, 24.04.2025
10:00 AM
Lecture room 1332
Place and time
On Thursdays:
WA 73, lecture room 1332, 10:00 - 12:00 am, in case of need until 2:00 pm
Moodle
We add all students who got a seat to the Moodle course, you can't join the course by yourself.