IBM SPSS Modeler Foundations V18.2 0A069G
- CMDBID 75717
- Course Code 0A069G
- Duration 2 Days
IBM Analytics DS&BA SPSS Course
course overview
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Overview
This course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.
. Explore more IBM training hereAudience
- Data scientists
- Business analysts
- Clients who are new to IBM SPSS Modeler or want to find out more about using it
Skills Gained
Introduction to IBM SPSS Modeler
- Introduction to data science
- Describe the CRISP-DM methodology
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
Prerequisites
- Knowledge of your business requirements
Outline
Introduction to IBM SPSS Modeler
- Introduction to data science
- Describe the CRISP-DM methodology
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
. Explore more IBM training hereCertification
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