TAYJ029 Practical Introduction to Data Mining 4 ECTS
Period I Period II Period III Period IV
Language of instruction
Type or level of studies
Postgraduate studies
Course unit descriptions in the curriculum
Yliopiston yhteiset tohtoriopinnot
Doctoral School

General description

Learning outcomes
After completing the course, the participants
- know the phases of the process of knowledge discovery (data prepocessing, data mining and postprocessing)
- know basic data mining tasks and methods
- are aware of possibilities of utilising data mining in different research fields


In data mining, large quantities of data are explored and analysed by automatic and semi-automatic means to discover novel, interesting information. Data mining is an interdisciplinary field combining e.g. methods from computer sciences and statistics. It has wide, diverse application areas from education, social, business and administrative sciences to medical and life sciences.

Course contents
-    Lectures 10 h
-    Hands-on exercises with data mining tools 10 h
-    Reading research articles related to applications of data mining methods in participant’s own field and writing a short report
-    Giving a presentation on applications of data mining in participant’s own field (presentation session 3 h)

Teachers: Kati Iltanen, Martti Juhola, Henry Joutsijoki

Target group

The course is intended for post-graduate students who are interested in data mining. No computer sciences or statistics background is required.

Enrolment: At the maximum 15 students. Selection method is draw.




Presentation session

Evaluation: Pass/fail