inf535 - Computational Intelligence I

Basics of statistics

At the end of the lecture period

Written or oral exam

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