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Lecturer(s)
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Juříková Martina, Ing. Ph.D.
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Course content
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Discussedtopics: -Data mining. Big data. Meaning of "mining and data mining ', conditions and process implementation and management of data mining company; -Specifics, possibilities and limits ofdata mining for small business; -Database Marketing and its connection with data mining in an offline environment -important types of information acquisition,analysis and interpretation for marketing decision; -Data mining in the online environment. What and how to "extract" from socialnetworks and online marketing; -Web mining -tools for deeper analysis and networking with CRM modules
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Learning activities and teaching methods
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unspecified
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| prerequisite |
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| Knowledge |
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| Prerequisities are not set. |
| Prerequisities are not set. |
| learning outcomes |
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| 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 |
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| 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 |
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| Knowledge |
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| Lecturing |
| Lecturing |
| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| Skills |
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| Lecturing |
| Lecturing |
| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| assessment methods |
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| Knowledge |
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| Composite examination (Written part + oral part) |
| Composite examination (Written part + oral part) |
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Recommended literature
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EAGLE, Nathan a Kate GREENE. Reality mining: using big data to engineer a better world. 2014. ISBN 9780262529839.
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WITTEN, I. H., Eibe FRANK, Mark A. HALL a Christopher J. PA. Data mining: practical machine learning tools and techniques.. 2017. ISBN 9780128042915.
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