Data on the course

Show instruction and examinations
521156S Towards Data Mining, 5 ECTS cr 
Code 521156S  Validity 01.08.2017 -
Name Towards Data Mining  Abbreviation Towards Data Mi 
Scope5 ECTS cr   
TypeAdvanced Studies Discipline4307 Information Engineering 
  Grading1 - 5, pass, fail 
Unit Computer Science and Engineering DP 

Satu Tamminen 

ECTS Credits 

5 ECTS credits

Language of instruction 



Autumn, period I.

Learning outcomes 

After completing this course, student can recognize data types and perform required pre-processing steps before further analysis:

  1. Student can design and implement a data collection process
  2. Student can combine data from different sources
  3. Student can normalize and transform data, and handle missing or incorrect values
  4. Student can ensure generalizability of the results

Course provides good ability to start Master’s Thesis or graduate studies. Topics at the course include data mining process in general level, data gathering and different data types, quality and reliability of the data, data preparation including the processing of missing values, outliers, and privacy issues, combination of signals from several sources, utilization of data bases in data mining process, and normalization and transformation of data and interdependence of the observations and their distributions. Additionally, topics concerning the generality of the results are covered, as well as, the principles of data division, for example, train-test-validate, cross-validation and leave-one-out methods.

Mode of delivery 

Lectures, independent work, group work

Learning activities and teaching methods 

16 h lectures, 16 h exercises, independent studying.

Target group 

The course is suitable for Master level students in Computer science and engineering study programmes, for minor subject studies or for doctoral students.

Prerequisites and co-requisites 

031021P Probability and Mathematical Statistics or similar

Recommended optional programme components 

The course is an independent entity and does not require additional studies carried out at the same time.

Recommended or required reading 

Lecture hand-out and exercise material will be provided. The course book will be announced in the beginning of the course. The material is in English. In addition to contact teaching, material for self-learning is available as well.

Assessment methods and criteria 

Weekly pre-lecture assignment + exercise submissions, and final exam. Half of the grade will be based on the submissions and half on the final exam.

Read more about assessment criteria at the University of Oulu webpage.


Numerical grading scale 1-5; zero stands for a fail.

Person responsible 

Tamminen Satu

Working life cooperation 


Other information 

Course learning environment is in Moodle



Current and future instruction
Functions Name Type ECTS cr Teacher Schedule
Registration Towards Data Mining  Course  Satu Tamminen  01.09.21 -20.10.21
registration period has not begun Towards Data Mining, Online course  Course  Satu Tamminen  08.09.21 -10.06.22

Future examinations
No examinations in WebOodi