Curriculum
- 1 Section
- 10 Lessons
- 16 Hours
Expand all sectionsCollapse all sections
- 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