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Vyučující
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Rodriguez Jorge Ricardo, Ph.D.
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Obsah předmětu
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1) Data visualization techniques in R 2) Basic concepts of regression analysis 3) Basic of data exploration in R 4) Techniques of data managing and transforming 5) Basics of data clustering. Clustering quality criteria 6) K-means, C-means and Hierarchical Clustering Algorithms in R 7) Density-Based DBSCAN and OPTICS Clustering Algorithms in R 8) Data Classification: Basic Concepts and Application with R 9) Basics of Fuzzy Logic. Steps of Fuzzy Inference Process Implementation 10) Practical Implementation of Fuzzy Inference Techniques Based on R Software Tools 11) Basics Concepts of Time Series Processing. Techniques of Time Series Analysis and Processing Based on R Software Tools 12) Applying Data Mining Techniques for Data Processing Based on R Software Tools
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Studijní aktivity a metody výuky
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nespecifikováno
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Výstupy z učení
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This e-learning course is focused to students who are planning to work as IT specialists in the fields related to analytics, data mining solutions, marketing etc., who want to learn about both the practical application and implementation of data mining methods based on one of the modern programming languages R. The aim of the course is to acquire knowledge and practical experience in the field of information processing, including the acquisition of useful skills. Software R offers a large number of methods for implementing of the functional programming paradigm during the corresponding project creation and implementation. For these reasons, the proposed course is actual and interesting for students who are focused to development and practical implementations of IT technologies based on R language. The course is available on moodle webpage by link: https://kacer.ujep.cz/course/view.php?id=65 . Přístup pro hosty: data_mining_R
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Předpoklady
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Basics of programming in R
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Hodnoticí metody a kritéria
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nespecifikováno
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Doporučená literatura
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