Computational Intelligence and Machine Learning

Course Syllabus

Course Code:Η14Ν
Semester:8th
ECTS units:5
Weekly Teaching Hours:4
Course Page:https://eclass.duth.gr/courses/TME241/
Instructors:AMANATIADIS AGGELOS

Περιγραφή Μαθήματος

The course provides an introduction to the principles and methodologies of Computational Intelligence and Machine Learning technologies (fuzzy systems, neural networks, deep learning and evolutionary algorithms) as well as the understanding and familiarization with the tools for the development of relevant applications.

Purpose of the course

The learning objectives:

  1. Understanding and distinguishing basic concepts, disciplines, methods, functions and applications of natural/artificial and computational intelligence and machine learning
  2. Recognises the nature and content of the problems and the approaches provided by AI and Machine Learning
  3. To get in touch with and learn about the function and applications of neural networks
  4. To get in touch with and learn about the operation and applications of evolutionary algorithms
  5. To get in touch with and learn about the operation and applications of fuzzy logic and fuzzy systems
  6. Search, study and synthesise articles from the international scientific literature on a scientific/technical problem. Manage bibliographic references correctly.
  7. Analyse the problem and synthesise the solution
  8. Use (program) specialised software to develop relevant applications
  9. Write technical reports and present his/her work
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