After completing the course (5 ECTS) a student - knows the phases of the process of knowledge discovery and understands its nature - knows basic data prepocessing, data mining and postprocessing tasks and methods - is able to apply these methods in practical knowledge discovery tasks
After completing the course (10 ECTS) a student - in addition to the above-mentioned outcomes - knows and is able to apply advanced methods used in the process of knowledge discovery - knows data management issues concerning knowledge discovery
Contents
Steps in the process of knowledge discovery: data preprocessing, data mining, postprocessing and knowledge utilisation. Preprocessing: data cleaning, integration, transformation and reduction. Data mining tasks and methods: association analysis, classification and clustering. Postprocessing: knowledge evaluation, interpretation and visualisation. Examples of knowledge discovery systems and practical application areas. Knowledge discovery and data management. Possibly other selected topics in knowledge discovery.
Teaching methods
Teaching method
Contact
Online
Lectures
40 h
0 h
Exercises
20 h
0 h
Teaching language
English
Modes of study
Option
1
Available for:
Degree Programme Students
Other Students
Open University Students
Doctoral Students
Exchange Students
weekly exercises, course assignment and examParticipation in course work