IBM SPSS Modeler Foundations (V18.2)

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

Please refer to course overview.

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

• Knowledge of your business requirements