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Intelligent Systems Engineering (4+1)

1. General information
 
The science for building artificial intelligent systems takes the central place in the engineering sciences. There are two major directions in artificial intelligent systems developments: one starts from machines and leads to intelligence – robotics' approach, ant the other starts from biological systems and leads towards building artificial beings – bioinformatics and biological engineering. This program includes both directions.

The scientific area of this study program is Intelligent Systems. This program contains two modules - one each for the different building approach. The first module represents the bioinformatics approach, ant the other one the robotics' approach. The studies are organized in two semesters. The number of ECTS of each module is 60. Each student will have 4 compulsory and 2 elective courses that are connected with the chosen master thesis.
 
Awarded degree: Master of Engineering Intelligent Systems – module Bioinformatics, or Master of Engineering Intelligent Systems – module Robotics
 
2. List of courses in study program

Compulsory courses for Intelligent Systems – Bioinformatics:
  • Semester 1
    • Intelligent Systems Computer Science
    • Information Processing in Biological Systems
    • Molecular Cell Biology
  • Semester 2
    • Bioinformatics Data Mining

Elective courses for Intelligent Systems – Bioinformatics:
  • Bioinformatics Modeling Techniques
  • Bioinformatics Data Mining
  • Machine Learning
  • Data Mining
  • Stochastic Processes
  • Molecular Cell Biology
  • Human– Robot Interaction
  • Robots Behavior
  • Math Fundamentals for Robotics
  • Robots Programming
 
Compulsory courses for Intelligent Systems – Robotics :
  • Semester 1
    • Intelligent Systems Computer Science
    • Information Processing in Biological Systems
    • Robotics Fundamentals
  • Semester 2
    • Robotics Perception
 
Elective courses for Intelligent Systems – Robotics
  • Bioinformatics Modeling Techniques
  • Bioinformatics Data Mining
  • Machine Learning
  • Data Mining
  • Stochastic Processes
  • Molecular Cell Biology
  • Human– Robot Interaction
  • Robots Behavior
  • Math Fundamentals for Robotics
  • Robots Programming