Communication Technology 1

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Communication Technologies 1

(Machine learning)

Creditability:

  • Computer Science Master's program: 4 SWS
  • Electrical Engineering Master's program: 4 SWS
  • Master Program Electrical Communication Engineering: 4 SWS(only for students starting before 2024)

Lecture type:

Lectures and presentations

Language:

By arrangement

Target audience:

  • Computer science - Computer engineering
  • Electrical Engineering - Communications Engineering
  • Master Program Electrical Communication Engineering(only for students starting before 2024)

Content:

The content of the lecture includes the following topics:

  • Introduction to machine learning
    • Collecting data
    • Nominal data
    • Time series
  • Introduction to writing scientific papers
  • Feature selection
  • Classification
    • Bayesian networks
    • Markov models
    • Decision trees
    • Neural networks
  • Clustering

Learning objectives:

  • Development of new content,
  • Presentation of content - both very important skills in the industry
  • Scientific work and publishing
  • Content: Overview of context recognition

Exam:

  • Presentation and 5 page paper
  • no written exam

Registration

Registration will take place in eCampus from 17.03.2026.


First event date

Thursday, 23.04.2026, 10:00 a.m., lecture hall 1332


Place and time

Thursdays:

WA 73, lecture room 1332, 10:00 - 12:00, until 14:00 if required


Moodle

Anyone who has been allocated a place will be entered in the Moodle course by us, there is no self-enrollment.


Responsible persons