IBM SPSS Modeler Foundations (V18.2) - 0A069G

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 executionCloud & Data PlatformData and AIInformation Architecture MarketAI Tools & Runtime PortfolioDecision Optimization