Com. Techn. 1Com. Techn. 1

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, 18.04.2024
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.


Person in charge

M.Sc. Dandan Liu