inf535 - Computational Intelligence I (Course overview)

inf535 - Computational Intelligence I (Course overview)

Department of Computing Science 6 KP
Module components Semester courses Examination
Lecture
  • No access 2.01.535 - Show lecturers
    • Prof. Dr. Oliver Kramer

    Dates on Monday, 06.03.2023 09:30 - 11:30
Exercises
  • No access 2.01.535 - Show lecturers
    • Prof. Dr. Oliver Kramer

    Dates on Monday, 06.03.2023 09:30 - 11:30
Hinweise zum Modul
Prerequisites
Basics of statistics
Prüfungszeiten
At the end of the lecture period
Module examination
Written or oral exam
Skills to be acquired in this module
After successful completion of the course, students should have acquired the ability to master the presented methods in theory and practice. The students should be able to recognize and model corresponding optimization and data analysis problems themselves and to apply the methods unerringly.

Professional competence
The students:
  • recognise optimisation problems
  • implement simple algorithms of heuristic optimisation
  • critically discuss solutions and selection of methods
  • deepen previous knowledge of analysis and linear algebra
Methodological competence
The students:
  • deepen programming skills
  • apply modelling skills
  • learn about the relation between problem class and method selection
Social competence
The students:
  • cooperatively implement content introduced in lecture
  • evaluate own solutions and compare them with those of their peers
Self-competence
The students:
  • evaluate own skills with reference to peers
  • realize personal limitations
  • adapt own problem solving approaches with reference to required method competences