Aims of knowledge discovery process, basic concepts and definitions. Applications view. Data processing. Basic technologies and its comparison with learning systems. Data clearing and transformation, attribute tests, error analysis. Decision and fuzzy decision trees. Decision rules and its conversion into decision tree. Rules generation. Searching algorithms. Clustering. Statistical technologies. Visualisation.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: Yes, for all

Participants prerequisite knowledge: Numerical methods (linear algebra, statistics) Domain-specific background knowledge