TKO_3103 Data Analysis and Knowledge Discovery 5 ECTS

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 data sets, and turn data into information and knowledge.

Contents

The course introduces methods and algorithms for extracting information and knowledge from large datasets. This includes techniques for 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

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 Biochemistry
Department of Future Technologies
Department of Biochemistry
Department of Future Technologies

Open enrolments

Oct 9, 2017 - Nov 5, 2017
2017–2018
Teaching
Department of Future Technologies
DP in Computer Science
DP in Computer Science
DP Bachelor of Science in Techn.(Communication St)
DP in Information and Communication Technology
MDP in Digital Health and Life Sciences (Tech.)
Finnish Study Modules