TIETS31 Knowledge Discovery 5–10 ECTS
Organised by
Degree Programme in Computer Sciences
Person in charge
Yliopistonlehtori Kati Iltanen
Preceding studies
Recommended:
The courses mentioned or equivalent courses.
Corresponding course units in the curriculum
School of Information Sciences
Curricula 2015 – 2017
TIETS31 Knowledge Discovery 5–10 ECTS

Learning outcomes

After completing the course (5 ECTS) a student
- knows the phases of the process of knowledge discovery and understands its nature
- knows basic data prepocessing, data mining and postprocessing tasks and methods
- is able to apply these methods in practical knowledge discovery tasks

After completing the course (10 ECTS) a student
- in addition to the above-mentioned outcomes
- knows and is able to apply advanced methods used in the process of knowledge discovery
- knows data management issues concerning knowledge discovery

Contents

Steps in the process of knowledge discovery: data preprocessing, data mining, postprocessing and knowledge utilisation.
Preprocessing: data cleaning, integration, transformation and reduction.
Data mining tasks and methods: association analysis, classification and clustering.
Postprocessing: knowledge evaluation, interpretation and visualisation.
Examples of knowledge discovery systems and practical application areas.
Knowledge discovery and data management.
Possibly other selected topics in knowledge discovery.

Teaching methods

Teaching method Contact Online
Lectures 40 h 0 h
Exercises 20 h 0 h

Teaching language

English

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
weekly exercises, course assignment and exam  Participation in course work 
In English

Evaluation

Numeric 1-5.

Belongs to following study modules

Faculty of Natural Sciences
Faculty of Communication Sciences
Faculty of Natural Sciences
Faculty of Natural Sciences
2017–2018
Teaching
Faculty of Natural Sciences