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Lecturer(s)
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Course content
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Data relevance aspects. Data modelling approaches, interweaving of approaches. Identification of data indicators for monitoring and evaluation. Methods and principles of data analytics. Data analytics of structured and unstructured data. Data analytics development trends.
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Learning activities and teaching methods
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Dialogic (discussion, interview, brainstorming), Laboratory work
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Learning outcomes
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The aim of the course is to introduce the terminology, basics of processing, and real-life applications of data processing in context of using spreadsheet na GIS tools. Selected processing methods are directly practiced on model situations by single student or in teams.
Doktorand je veden k samostatné práci při zpracování projektu z probírané látky, kdy získané poznatky zároveň využije pro svou doktorskou disertační práci. V rámci řešení projektu samostatně vyhledává problémy řešitelné metodami obsaženými v předmětu, prezentuje dílčí i konečná řešení svého projektu, získané poznatky obhajuje v odborné diskuzi.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Home assignment evaluation, Self project defence
Students within the project independently search problems solvable by means of methods contained in a course, present the partial and final solution, ideas advocate in discussion.
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Recommended literature
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