Data Structures or equivalent required. It is recommended that students have completed the basic courses in Mathematics and Statistics before taking this course.
Corresponding course units in the curriculum
School of Information Sciences
Curricula
2015 –
2017
The student learns the premises, objectives and relevance as well as the basic methods of data mining.
Contents
Properties of data and measurements are considered. Preprocessing methods of data are described to select and prepare data for data mining algorithms. Some data mining algorithms are presented as well as their applications, for instance, for classification and prediction of data.
Teaching methods
Teaching method
Contact
Online
Lectures
24 h
0 h
Exercises
10 h
0 h
Offered every second or third year.
Teaching language
English
Modes of study
Option
1
Available for:
Degree Programme Students
Other Students
Open University Students
Doctoral Students
Exchange Students
Lectures, weekly excercises and examParticipation in course work
In
English
Written examination and completed weekly exercises.
Evaluation
Numeric 1-5.
Study materials
Dorian Pyle: Data Preparation for Data Mining, Morgan Kaufmann Publishers, 1999
Ian H. Witten, Eibe Frank, Mark A. Hall: Data Mining, Practical Machine Learning Tools and Techniques, third edition, Morgan Kaufmann Publishers, 2011