Curricula Guides
2015–2016
Archived Curricula Guide 2012–2015
Curricula Guide is archieved. Please refer to current Curricula Guides
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School of Information Sciences 2012–2015
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Advanced Studies in Computational Methods and Programming
TIETS11
Data mining
10
ECTS
Organised by
Degree Programme in Computer Sciences
Person in charge
Professor Martti Juhola
Preceding studies
Compulsory:
TIETA6
Data Structures
Corresponding course units in the curriculum
Learning outcomes
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
FinnishModes 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.
Evaluation
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
School of Information Sciences
School of Information Sciences
School of Information Sciences
2015–2016
Archived Teaching Schedule. Please refer to current Teaching Shedule.
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School of Information Sciences