Deze cursusinformatie geeft aan hoe het onderwijs zal verlopen bij pandemieniveau code geel en groen.
Als er tijdens het academiejaar aangepast wordt naar code oranje of rood, zijn er wijzigingen mogelijk o.a. in de gebruikte werk - en evaluatievormen.

Data mining

Course Code :2103TEWDAS
Study domain:Computer Science
Academic year:2020-2021
Semester:1st semester
Contact hours:60
Study load (hours):168
Contract restrictions: No contract restriction
Language of instruction:English
Exam period:exam in the 1st semester
Lecturer(s)David Martens

3. Course contents *

In the past decade we’ve witnessed a huge increase in the amount of data being captured and stored. In these large datasets very useful knowledge is present, though often concealed in the vastness of the data. With data mining techniques patterns are automatically revealed from such large datasets.

First, data mining techniques and applications are discussed. Next we will go into popular predictive and descriptive data mining techniques, with applications in marketing and risk management. Also analyses such as social network analysis, text mining, process mining and Big Data will be looked at.

Basic programming skills in Python will be learnt. The learned concepts, techniques and programming language will be applied and evaluated with a real-life case.