Detailed Course Outline
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