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

At the end of the course, participants will be able to :

• Collect initial data
• Understand data
• Define the unit of analysis
• Integrate data
• Transform fields
• Examine the relationship between a categorical field and a continuous field
• Discover modeling
• Improving efficiency

• 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
• Basic understanding of Data Science