Schulung - IBM 0A008G - Introduction to IBM SPSS Modeler and Data Science (v18.1.1)

Course Outline

1. Introduction to data scienceList two applications of data scienceExplain the stages in the CRISP-DM methodologyDescribe the skills needed for data science2. Introduction to IBM SPSS ModelerDescribe IBM SPSS Modeler's user-interfaceWork with nodes and streamsGenerate nodes from outputUse SuperNodesExecute streamsOpen and save streamsUse Help3. Introduction to data science using IBM SPSS ModelerExplain the basic framework of a data-science projectBuild a modelDeploy a model4. Collecting initial dataExplain the concepts data structure, of analysis, field storage and field measurement levelImport Microsoft Excel filesImport IBM SPSS Statistics filesImport text filesImport from databasesExport data to various formats5. Understanding the dataAudit the dataCheck for invalid valuesTake action for invalid valuesDefine blanks6. Setting the of analysisRemove duplicate recordsAggregate recordsExpand a categorical field into a series of flag fieldsTranspose data7. Integrating dataAppend records from multiple datasetsMerge fields from multiple datasetsSample records8. Deriving and reclassifying fieldsUse the Control Language for Expression Manipulation (CLEM)Derive new fieldsReclassify field values9. Identifying relationshipsExamine the relationship between two categorical fieldsExamine the relationship between a categorical field and a continuous fieldExamine the relationship between two continuous fields10. Introduction to modelingList three types of modelsUse a supervised modelUse a segmentation model

Objective

• Introduction to data science
• Introduction to IBM SPSS Modeler
• Introduction to data science using IBM SPSS Modeler
• Collecting initial data
• Understanding the data
• Setting the of analysis
• Integrating data
• Deriving and reclassifying fields
• Identifying relationships
• Introduction to modeling