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Lecturer(s)
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Kašparová Miloslava, Ing. Ph.D.
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Petr Pavel, doc. Ing. Ph.D.
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Course content
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Basic concepts and principles of working with data files. Basic data processing in spreadsheet MS Excel (eg use of functions, data filtering, creation of pivot tables, data visualization). Classification of data. Data analysis in corresponding software (eg IBM SPSS Statistics, MS Excel). Evaluation of analysis results and their graphical representation (visualization of results).
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities, Laboratory work
- Contact teaching
- 39 hours per semester
- Data/material collection
- 20 hours per semester
- Home preparation for classes
- 15 hours per semester
- Independent critical reading
- 10 hours per semester
- Term paper
- 66 hours per semester
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Learning outcomes
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The aim of the course is to consolidate the knowledge and extend the skills of data collection, analysis and processing, design models and their verification by using the tools of Data Mining and Business Intelligence.
Students will consolidate their knowledge and extend practical skills in the field of data collection, their analysis and processing, model design and verification and interpretation of conclusions. They will learn how to effectively use Data Mining tools in this area. They will learn to work in solving tasks in work teams, which will extend their competencies in the field of team work.
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Prerequisites
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Basic knowledge of systems theory II, Data Mining II and Business Intelligence.
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Assessment methods and criteria
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Written examination, Systematic monitoring, Self project defence
Assignment: successful elaboration of given tasks (provided in Stag).
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Recommended literature
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Brož, M. Microsoft Excel pro manažery a ekonomy. Computer Press. ISBN 80-251-1307-8.
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HENDL, J. Přehled statistických metod zpracování dat. Analýza a metaanalýza dat. Praha: Portál, 2004.
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Petr, P. Data Mining 1. Pardubice: Univerzita Pardubice, 2006.
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Petr, P. Metody Data Miningu: část II. Pardubice: Univerzita Pardubice, 2014.
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Petr, P. Metody Data Miningu: část I. Pardubice: Univerzita Pardubice, 2014.
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Řehák, J., Brom, O. SPSS: praktická analýza dat. Brno: Computer Press., 2015.
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Řezanková, Hana. Analýza dat z dotazníkových šetření. Praha. 2017.
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