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Archived Curricula Guide 2012–2015
Curricula Guide is archieved. Please refer to current Curricula Guides
TIETS11 Data mining 10 ECTS
Organised by
Degree Programme in Computer Sciences
Person in charge
Professor Martti Juhola
Preceding studies
It is recommended that students have completed the obligatory basic courses in Mathematics before taking this course.
Corresponding course units in the curriculum
School of Information Sciences
Curricula 2011 – 2012
TKOPS126 Data Mining 10 ECTS

Learning outcomes

The student learns the premises, objectives and relevance as well as the basic methods of data mining.


The relevance and definitions of data and data measurement, visualisation and analysis of data, unstructured and incomplete data, data mining algorithms, models and patterns, scoring functions of data mining algorithms, searching and optimisation methods, descriptive modelling, predictive modelling of classification, data management and databases in conjunction with data mining, searching for patterns and rules, and searching on the basis of contents.

Teaching methods

Teaching method Contact Online
Lectures 48 h 0 h
Exercises 20 h 0 h

Teaching language


Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Self-studying, weekly excercises and exam  Participation in course work 
In Finnish
Further information 

Viikkoharjoitukset ja kirjallinen kuulustelu.

In English

Written examination and completed weekly exercises.


Numeric 1-5.

Study materials

Hand D., Mannila H. & Smyth P., Principles of Data Mining. MIT Press 2001.

Belongs to following study modules

School of Information Sciences
Archived Teaching Schedule. Please refer to current Teaching Shedule.
School of Information Sciences