Data Mining

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Code	Completion	Credits	Range	Language
DA-DMI	Z,ZK	6	30KP+30KC	English

Garant předmětu:

Michal Valenta

Lecturer:

Tutor:

Michal Valenta

Supervisor:

Department of Software Engineering

Synopsis:

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.

Teaching takes place at University of Antwerpen.

See the web page https://www.uantwerpen.be/en/study/programmes/all-programmes/digital-business-engineering/about-the-programme/study-programme/

Requirements:

Syllabus of lectures: