Data mining

Type of study	Follow-up Master
Language of instruction	Czech
Code	157-0386/02
Abbreviation	DM
Course title	Data mining
Credits	5
Coordinating department	Department of Systems Engineering and Informatics
Course coordinator	doc. dr hab. Maria Antonina Mach-Król

Osnova předmětu

1. Introduction (definition of data mining, relation to the other scientific disciplines, clarification of the basic concepts).
2. Data, data transformation, normalization, distance measures, similarity measures, etc.
3. Data mining (general): data mining processes (SEMMA, CRISP-DM, etc.), data mining tasks.
4. Association rules
5. Classification
6. Clustering
7. Detection of outliers
8. Text mining, sentiment analysis
9. Environment of software tools and languages
10. Future trends in data mining

E-learning

Students have all relevant presentations from lectures and instructions in LMS Moodle

Povinná literatura

BRAMER, Max. Principles of data mining. London: Springer-Verlag, 2020. ISBN: 978-1-4471-7492-9.
LENDAVE Vijaysinh. Beginner's Guide to WEKA - A Tool for ML and Analytics. Delhi: Analztics India, 2023 - online podporní material.

Advised literature

KUMAR Jugnesh. Data Warehouse and Data Mining: Concepts, techniques and real life applications. Uttar Pradesh: PB Publications, 2023. .
HUDEC, Miroslav. Fuzziness in Information Systems - How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization. Cham: Springer, 2016.
AGGRAWAL, Charu. Data Mining: The Textbook. Cham: Springer, 2015. .

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