The student learns the premises, objectives and relevance as well as the basic methods of data mining.
Contents
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
Finnish
Modes of study
Option
1
Available for:
Degree Programme Students
Other Students
Open University Students
Doctoral Students
Exchange Students
Self-studying, weekly excercises and examParticipation in course work
In
Finnish
Further information
Viikkoharjoitukset ja kirjallinen kuulustelu.
In
English
Written examination and completed weekly exercises.
Evaluation
Numeric 1-5.
Study materials
Hand D., Mannila H. & Smyth P., Principles of Data Mining. MIT Press 2001.