Principles of Data Mining

Total Hours in Course81

Number of hours for lectures16

Number of hours for seminars and practical classes16

Independent study hours49

Date of course confirmation12.01.2016

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

lect.

Ingus Šmits

Mg. sc. ing.

Course abstract

In this course principles of data mining are introduced. Students learn how to find solutions for data mining tasks and how to analyze obtained results. In practical exercises different data mining algorithms are created in C# programming language and used in real data analyze tasks.

Learning outcomes and their assessment

• Knowledge of data mining principles;
• skills in finding correct solution for data mining tasks;
• competence in using data mining algorithms for solving specific problems and in analyzing obtained results.

Compulsory reading

1. McKnight P.E., McKnight M., Sidani S., Figueredo A.J. Missing Data. A gentle introduction. The Guilford press, New York, London, 2007.
2. Bramer M. Principles of Data Mining, London: Springer Verlag, 2007.
3. Барсегян А.А., Куприянов М.С., Цтепаненко Б.Б., Холод И. И. Технологии анализа данних: Data Mining, Visual Mining, Text Minig, Olap, Санкт-Петербург: БХВ- Петербург, 2007. 375 c.