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FIT-ZZNAcad. year: 2009/2010
Basic concepts concerning knowledge discovery in data, relation of knowledge discovery and data mining. Data sources for knowledge discovery. Principles and techniques of data preprocessing for mining. Systems for knowledge discovery in data, data mining query languages. Data mining techniques – characterization and discrimination, association rules, classification and prediction, clustering. Complex data type mining. Trends in data mining. Working-out a data mining project by means of an available data mining tool.
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branch MBI , 2 year of study, winter semester, compulsorybranch MBS , 0 year of study, winter semester, compulsory-optionalbranch MGM , 2 year of study, winter semester, electivebranch MGM , 2 year of study, winter semester, electivebranch MIN , 2 year of study, winter semester, compulsorybranch MIN , 2 year of study, winter semester, compulsorybranch MIS , 2 year of study, winter semester, compulsory-optionalbranch MIS , 2 year of study, winter semester, electivebranch MMI , 0 year of study, winter semester, electivebranch MMM , 0 year of study, winter semester, electivebranch MPS , 0 year of study, winter semester, electivebranch MPV , 1 year of study, winter semester, compulsory-optionalbranch MSK , 2 year of study, winter semester, compulsory-optional
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