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Data Mining: Artificial Intelligence

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First lecture on Friday, 25th April.

 

This course continues the lecture "Principles of Data Mining" of the winter term. Please note that the latter is a prerequisite for it.

Overview

Effort: SWS 2, Credits 4

Course type:  Lecture (Bachelor/Master)

Language: english

Exam: written

Content

The course aims at introducing the methods of Artificial Intelligence and Soft Computing (Fuzzy Systems, Neural Networks, Evolutionary Algorithms) for clustering, classification, data explanation and prediction. The plan of the course is as follows:

25.04

Overview of the course / Introduction to Fuzzy Logic

02.05

no lecture (holiday)

09.05

Fuzzy Systems 

16.05

Exercise 1 (Fuzzy Systems)

23.05

Neural Networks 1

30.05

no lecture (holiday)

06.06

Neural Networks 2

13.06

Neural Networks 3

20.06

Exercise 2 (Neural Networks)

27.06

Metaheuristics 1

04.07

Metaheuristics 2

11.07

Exercise 3 (Metaheuristics)

18.07

Q&A

25.07

Exam

 

Literature

  • For all topics: Michael Berthold, David Hand: Intelligent Data Analysis, An Introduction, 2te Auflage, Springer-Verlag, 2003.
  • Online book Fuzzy Logic (german) partly very theoretical
  • Book about neuronal networks (and fuzzy systems) (german): Detlef Nauck, Christian Borgelt, Frank Klawonn und Rudolf Kruse.: Neuro-Fuzzy-Systeme - Von den Grundlagen Neuronaler Netze zu modernen Fuzzy-Systemen Vieweg-Verlag, Wiesbaden, Germany 2003, ISBN 3-528-25265-0
  • Another script to neuronal networks (german) Ein kleiner Überblick über Neuronale Netzwerke

Course criteria

  • 50% votations exercise sheets
  • active participation in the exercise
  • Oral exam or written exams at the end of the semester

Prerequisites

Basic mathematical skills (statistics), course "Principles of Data Mining" or "Data Mining: Foundations"