Curriculum
- 1 Section
- 10 Lessons
- 16 Hours
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- Topics10
- 1.1Introduction 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
- 1.2Collect initial data Describe field storage Describe field measurement level Import from various data formats Export to various data formats
- 1.3Understand the data Audit the data Check for invalid values Take action for invalid values Define blanks
- 1.4Set the unit of analysis Remove duplicates Aggregate data Transform nominal fields into flags Restructure data
- 1.5Integrate data Append datasets Merge datasets Sample records
- 1.6Transform fields Use the Control Language for Expression Manipulation Derive fields Reclassify fields Bin fields
- 1.7Further field transformations Use functions Replace field values Transform distributions
- 1.8Examine relationships Examine the relationship between two categorical fields Examine the relationship between a categorical and continuous field Examine the relationship between two continuous fields
- 1.9Introduction to modeling Describe modeling objectives Create supervised models Create segmentation models
- 1.10Improve 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
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
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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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