Data Science Course Overview-1

1. Introduction • DataScienceisaninterdisciplinaryfieldthatusesscientificmethods,processes,algorithms,andsystemstoextractknowledgeandinsightsfromstructuredandunstructureddata.ADataSciencecourseisdesignedtoprovidestudentswiththeskillsandknowledgenecessaryto understand,analyze,andinterpretdata.Thiscoursetypicallycoversvariousdomains,including statistics,machinelearning,datavisualization,andbigdatatechnologies. • CourseObjectives • TheprimaryobjectivesofaDataSciencecourseareto: • Equipstudentswiththeabilitytohandleandanalyzelargedatasets. • Teachstudentshowtousestatisticalmethodstoderivemeaningfulinsightsfromdata. • Provideastrongfoundationinmachinelearningtechniques. • Developskillsindatavisualizationtocommunicatefindingseffectively. • Introducebigdatatechnologiesandtoolsusedintheindustry. • Curriculum • Introduction toData Science • Definitionandimportance ofData Science. • Overviewofthedatascienceprocess. • DataSciencevs.BusinessIntelligence. • StatisticsandProbability • Descriptivestatistics:mean,median,mode,variance,andstandarddeviation. • Probabilitytheoryanddistributions:normal,binomial,Poisson. • Hypothesistestingandconfidenceintervals. • DataWranglingandExploration • Datacollectionandcleaning. • Handlingmissingvaluesandoutliers. • Data transformation and normalization. • ExploratoryDataAnalysis(EDA)techniques. • ProgrammingforData Science • IntroductiontoprogramminglanguagescommonlyusedinDataScience(Python/R). • Essentiallibraries:NumPy,Pandas,Scikit-learn(Python),andtidyverse(R). • Writingefficientandreadablecodefordataanalysis. • MachineLearning • Supervisedlearning:regressionandclassificationalgorithms. • Unsupervisedlearning:clustering anddimensionalityreduction. • Modelevaluationandvalidationtechniques.

2. -Introductiontoneuralnetworksanddeeplearning. • DataVisualization • ImportanceofdatavisualizationinDataScience. • Toolsandlibraries:Matplotlib,Seaborn,Plotly(Python),ggplot2(R). • Designingeffective andinformativevisualizations. • Storytellingwithdata. • BigDataTechnologies • Introductiontobigdata concepts. • Toolsandframeworks:Hadoop,Spark. • WorkingwithNoSQLdatabases:MongoDB,Cassandra. • StreamprocessingwithApacheKafka. • CapstoneProject • Applyinglearnedskillstoareal-worlddatascienceproject. • Problemformulation,datacollection,andpreprocessing. • Modelbuilding,evaluation,anddeployment. • Presentation offindingsandinsights. • TeachingMethodology • ADataSciencecourseinmumbaitypicallyinvolvesamixoftheoreticallessonsandpractical exercises.Studentsengageinhands-onprojectsandlabstoapplytheconceptslearnedin class.Collaborationongroupprojectsandpeerreviewsisoftenencouragedtofosteradeeper understandingofthematerial. Additionally, guestlecturesfromindustryprofessionalsprovide insightsintoreal-worldapplicationsofDataScience. • CareerProspects • CompletingaDataSciencecourseopensupnumerouscareeropportunities.Graduatescan pursuerolessuchas: • DataScientist • DataAnalyst • MachineLearningEngineer • BusinessIntelligenceAnalyst • DataEngineer • Theserolesareinhighdemandacrossvariousindustries,includingfinance,healthcare, e-commerce,andtechnology. • Conclusion

3. ADataSciencecourseprovidesacomprehensiveeducationindataanalysis,machinelearning, andbigdatatechnologies.Bytheendofthecourse,studentsare well-equippedtotackle complexdatachallengesandderiveactionableinsights,makingthemvaluableassetstoany organization.TheinterdisciplinarynatureofDataScienceensuresthatgraduatescanadapt to variousrolesandindustries,drivinginnovationanddecision-makingthroughdata-driven approaches. IfyouneedmorespecificinformationaboutaparticularDataSciencecourse,suchastheone offeredbyExcelR,pleaseletmeknow! BusinessName:ExcelR-DataScience,DataAnalytics,BusinessAnalystCourseTraining Mumbai Address:Unitno.302,03rdFloor,AshokPremises,OldNagardasRd,NicolasWadiRd, MograVillage,GundavaliGaothan,AndheriE,Mumbai,Maharashtra400069,Phone: 09108238354,Email:enquiry@excelr.com.