IBM SPSS Modeler Foundations (V18.2) – 0A069G CR

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Course Code: 0A069G Brand: DS&BA – SPSS Category: Analytics Skill Level: Basic Duration: 16H Modality: CR     Audience

  • Data scientists
  • Business analysts
  • Clients who are new to IBM SPSS Modeler or want to find out more about using it

  Prerequisites

  • Knowledge of your business requirements

  Short Summary

This course teaches how to use IBM SPSS Modeler 18.2.   Overview

This course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.

  Topic

Introduction to IBM SPSS Modeler• Introduction to data science• Describe the CRISP-DM methodology• Introduction to IBM SPSS Modeler• Build models and apply them to new dataCollect initial data• Describe field storage• Describe field measurement level• Import from various data formats• Export to various data formatsUnderstand the data• Audit the data• Check for invalid values• Take action for invalid values• Define blanksSet the unit of analysis• Remove duplicates• Aggregate data• Transform nominal fields into flags• Restructure dataIntegrate data• Append datasets• Merge datasets• Sample recordsTransform fields• Use the Control Language for Expression Manipulation• Derive fields• Reclassify fields• Bin fieldsFurther field transformations• Use functions• Replace field values• Transform distributionsExamine relationships• Examine the relationship between two categorical fields• Examine the relationship between a categorical  and continuous field• Examine the relationship between two continuous fieldsIntroduction to modeling• Describe modeling objectives• Create supervised models• Create segmentation modelsImprove efficiency• Use database scalability by SQL pushback• Process outliers and missing values with the Data Audit node• Use the Set Globals node• Use parameters• Use looping and conditional execution

  Objectives

Introduction to IBM SPSS Modeler • Introduction to data science • Describe the CRISP-DM methodology • Introduction to IBM SPSS Modeler • Build models and apply them to new data  

Collect initial data • Describe field storage • Describe field measurement level • Import from various data formats • Export to various data formats  

Understand the data • Audit the data • Check for invalid values • Take action for invalid values • Define blanks  

Set the unit of analysis • Remove duplicates • Aggregate data • Transform nominal fields into flags • Restructure data  

Integrate data • Append datasets • Merge datasets • Sample records

 

Transform fields • Use the Control Language for Expression Manipulation • Derive fields • Reclassify fields • Bin fields  

Further field transformations • Use functions • Replace field values • Transform distributions  

Examine relationships • Examine the relationship between two categorical fields • Examine the relationship between a categorical and continuous field • Examine the relationship between two continuous fields  

Introduction to modeling • Describe modeling objectives • Create supervised models • Create segmentation models  

Improve efficiency • Use database scalability by SQL pushback • Process outliers and missing values with the Data Audit node • Use the Set Globals node • Use parameters • Use looping and conditional execution

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