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Modulecode SS-4314 ModuleTitle DataMining Degree/Diploma BachelorofScience(ComputerScience) TypeofModule MajorOption ModularCredits 4 TotalstudentWorkload 10 hours/week Contacthours 4 hours/week Prerequisite SS-2202AlgorithmsandDataStructures SS-2203DatabaseDesign SS-2207IntroductiontoArtificialIntelligenceandSoftComputing Anti-requisite None Aims Thismodulecoverspracticalapproachesofdataminingwiththeapplicationofmachinelearning techniquesforanalyzingdatatodetermineunknownpropertiesaboutthedata. ThismoduleisacompulsorymoduleforSoftComputingstream. LearningOutcomes Onsuccessfulcompletionofthismodule,astudentwillbeexpectedtobeableto: Lowerorder: 20% - differentiatebetweendataminingandmachinelearning - understandhowdataminingalgorithmswork - understandandapplyperformanceimprovementtechniquesincludingpreprocessingofinputandaggregatingoutputfromdifferentmethods - understandthedifferentprocessesinhandlingdataforextractionofuseful information,includingintelligentdataanalysisandmodelling Middleorder:60% - usedataminingtoolssuchasWekaandRtodevelopdatamining applications - selectappropriateapproachestoparticularproblems;analyseandevaluate theresultsofdifferenttechniques Higherorder: 20% - designandimplementdataminingtechniques,basedontherequirements ofthedata(definingtheproblem) ModuleContents - Introductiontodatamininganditsapplications;dataminingtechnologies; - Machinelearningandstatistics;clusteringandclassification; - Evaluatingdataminingalgorithmsandvalidatingresults - Ensemblemethods;featureextractionandselection;WekaandR Assessment Formative assessment InteractiveQuizzesandFeedback Summative assessment Examination:50% Coursework:50% - 2classtests(20%) - 1writtenassignment(15%) - 1laboratoryexercise(15%)