Download Course Title Data Mining over Structured and Un

CourseTitle
CourseID
Instructor
DataMiningoverStructuredandUn-StructuredData
CIT-653
Dr.SamhaaEl-Beltagy
CIT-INFORMATICS
Elective
SpringSemester,2015
Program
Type
StartOffering
Pre-requisites:
“IntroductiontoMachineLearningandStatisticalDataAnalysis”
BriefDescription
DataMininggenerallyreferstotheprocessofexploringpatternsandregularitiesin
dataforenablingforecasting,predication,andprovidingabetterunderstandingof
thedataforguidingdecisionmaking.Thiscourseprovidesanintroductiontodata
mining concepts over structured and un-structured data with special emphasis on
practicalapplicationsofthisimportantresearcharea.DataMiningusuallyinvolves
the extraction and discovery of useful knowledge from raw data. The discovery
process, also known as knowledge discovery, includes feature selection, data
cleaning,andcodingandentailstheuseofdifferentstatisticalandmachinelearning
techniques. The course will cover these areas. Throughout the whole process,
students will be provided with examples which will serve to illustrate concepts
being introduced. Students will also learn how to solve real-life problems using
state-of-the-arttechnologiesfordataanalyses.
GradingSystem
10%Attendanceandparticipation
15%Midterm
40%Assignmentsandprojects
25%Final
Textbook
“MiningofMassiveDataset,"byAnandRajaramanandJeffreyD.Ullman;Cambridge
UniversityPress,2011.
“DataMining:PracticalMachineLearningToolsandTechniques(SecondEdition)”byIan
H.WittenandEibeFrank,MorganKaufmann,2005.
COURSECONTENTS
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Dataminingconcepts
SimilarityMeasuresonbigscale
Miningdatastreams
Webanalytics:pagerank,extractingknowledgefromtheweb,spam
analysis
Datacleaningandpre-processing
Associationrulemining
Advertisingontheweb
Recommendationsystemsfore-commerce