The subject is taught in Polish

Lecture

The course aims to introduce students to data mining methods and processes. It presents the main data mining tasks, such as prediction, classification, and segmentation, as well as the algorithms used in these tasks.

The lecture covers the following topics:

  1. Basic data mining issues 
  2. The data mining process and its role within an organization 
  3. Forms of data and knowledge representation 
  4. Overview of the basic types of decision classifiers 
  5. Decision trees 
  6. Decision rules 
  7. Association rules 
  8. Data grouping 
  9. An example of numerical methods in data mining 
  10. Sources and nature of errors in the data mining process 
  11. Input and output engineering 
  12. Other data mining techniques

Laboratory

In the labs, students learn tools for data mining and designing data flows for the mining process. Various mining algorithms are used in the labs, including decision tree construction, rule extraction, and segmentation. In addition to the exercises, students have the opportunity to analyze assigned or selected data sets and attempt to achieve their mining goals.