Uusi opinto-opas (sisältäen myös opetusohjelmat) lukuvuodelle 2018-2019 sijaitsee osoitteessa https://opas.peppi.utu.fi . Tältä sivustolta löytyvät enää vanhat opinto-oppaat ja opetusohjelmat.

The new study guide (incl. teaching schedules) for academic year 2018-2019 can be found at https://studyguide.utu.fi. This site contains only previous years' guides.

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Archived Curricula Guide 2013–2014
Curricula Guide is archieved. Please refer to current Curricula Guides
TKO_3103 Data Analysis and Knowledge Discovery 6 ECTS
Organised by
Computer Science
Person in charge
Jukka Heikkonen

Learning outcomes

This course enables to learn when and how to apply state of the art data analysis and knowledge discovery tools for data. Students will learn modern data analysis methods and algorithms to discover patterns and trends in large, complex and high-dimensional datasets, and turn data into information and knowledge.

Contents

The course introduces methods and algorithms for extracting information and knowledge from large datasets. This includes statistical, information theoretical and Bayesian techniques combined with data compression, visualization, classification, regression, outlier detection, rule induction, model complexity selection, and model validation.

Teaching methods

Teaching method Contact Online
Lectures 28 h 0 h
Exercises

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Written exam
  • In English
Project / practical work
  • In English
English:
Written exam and Project / practical work

Written exam and project work.

Evaluation

Numeric 0-5.

Study materials

M.R. Berthold, C. Borgelt, F. Höppner, F. Klawonn: Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data. Springer, London (2010) 

Belongs to following study modules

Department of Future Technologies
Department of Future Technologies
Department of Future Technologies
Pakolliset syventävät opinnot (Computer Science)
Department of Future Technologies
2013–2014
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Department of Future Technologies
DP in Computer Science
DP in Electr. and Communication Technology
Finnish Study Modules