Course: Data Mining

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Course title Data Mining
Course code KUMK/MKDTM
Organizational form of instruction Seminary
Level of course unspecified
Year of study not specified
Semester Summer
Number of ECTS credits 3
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Juříková Martina, Ing. Ph.D.
Course content
- Data mining, Big data, the meaning of "data mining and extraction", the conditions and process of implementing and managing data mining in the company; - specifics, possibilities and limits of data mining for a small company; - database marketing and its connection with data mining in the offline environment - important types of information, their acquisition, analysis and interpretation for marketing decisions; - Data mining in the online environment, what and how to "benefit" from social networks and online marketing; - Web mining - tools for deeper analysis and connection with CRM modules.

Learning activities and teaching methods
unspecified
prerequisite
Knowledge
Prerequisities are not set.
Prerequisities are not set.
learning outcomes
Knowledge of the concept of data mining
Knowledge of the concept of data mining
Knowledge of data mining techniques
Knowledge of data mining techniques
Knowledge of the benefits of data mining
Knowledge of the benefits of data mining
Knowledge of the most common areas of application of data mining
Knowledge of the most common areas of application of data mining
Knowledge of data mining efficiency measurement options
Knowledge of data mining efficiency measurement options
Skills
Explain the principle of data mining
Explain the principle of data mining
Explain the difference between data mining and other research techniques
Explain the difference between data mining and other research techniques
Create a data mining usage plan
Create a data mining usage plan
Design appropriate data mining methods
Design appropriate data mining methods
Design a way to measure the effectiveness of data mining
Design a way to measure the effectiveness of data mining
teaching methods
Knowledge
Lecturing
Lecturing
Dialogic (Discussion, conversation, brainstorming)
Dialogic (Discussion, conversation, brainstorming)
Skills
Lecturing
Lecturing
Dialogic (Discussion, conversation, brainstorming)
Dialogic (Discussion, conversation, brainstorming)
assessment methods
Knowledge
Composite examination (Written part + oral part)
Composite examination (Written part + oral part)
Recommended literature
  • Dostál, Petr. Soft computing v podnikatelství a veřejné správě. Brno. Akademické nakladatelství CERM, 2015. ISBN 978-80-7204-896-0.
  • EAGLE, Nathan a Kate GREENE. Reality mining: using big data to engineer a better world. 2014. ISBN 9780262529839.
  • WITTEN, I. H. Data mining: practical machine learning tools and techniques. Fourth Edition. Amsterdam: Elsevier, 2017. ISBN 9780128042915.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester