IBM SPSS Modeler Foundations (V18.2)0A069GIBIBMIB-0A069G1<ul>
<li>Knowledge of your business requirements</li></ul><ul>
<li>Data scientists</li><li>Business analysts</li><li>Clients who are new to IBM SPSS Modeler or want to find out more about using it</li></ul><p>Introduction to IBM SPSS Modeler
</p>
<ul>
<li>• Introduction to data science</li><li>• Describe the CRISP-DM methodology</li><li>• Introduction to IBM SPSS Modeler</li><li>• Build models and apply them to new data</li></ul><p>
Collect initial data
</p>
<ul>
<li>• Describe field storage</li><li>• Describe field measurement level</li><li>• Import from various data formats</li><li>• Export to various data formats</li></ul><p>
Understand the data
</p>
<ul>
<li>• Audit the data</li><li>• Check for invalid values</li><li>• Take action for invalid values</li><li>• Define blanks</li></ul><p>
Set the unit of analysis
</p>
<ul>
<li>• Remove duplicates</li><li>• Aggregate data</li><li>• Transform nominal fields into flags</li><li>• Restructure data</li></ul><p>
Integrate data
</p>
<ul>
<li>• Append datasets</li><li>• Merge datasets</li><li>• Sample records</li></ul><p>
Transform fields
</p>
<ul>
<li>• Use the Control Language for Expression Manipulation</li><li>• Derive fields</li><li>• Reclassify fields</li><li>• Bin fields</li></ul><p>
Further field transformations
</p>
<ul>
<li>• Use functions</li><li>• Replace field values</li><li>• Transform distributions</li></ul><p>
Examine relationships
</p>
<ul>
<li>• Examine the relationship between two categorical fields</li><li>• Examine the relationship between a categorical and continuous field</li><li>• Examine the relationship between two continuous fields</li></ul><p>
Introduction to modeling
</p>
<ul>
<li>• Describe modeling objectives</li><li>• Create supervised models</li><li>• Create segmentation models</li></ul><p>
Improve efficiency
</p>
<ul>
<li>• Use database scalability by SQL pushback</li><li>• Process outliers and missing values with the Data Audit node</li><li>• Use the Set Globals node</li><li>• Use parameters</li><li>• Use looping and conditional execution</li></ul><p>Introduction to IBM SPSS Modeler
</p>
<ul>
<li>• Introduction to data science</li><li>• Describe the CRISP-DM methodology</li><li>• Introduction to IBM SPSS Modeler</li><li>• Build models and apply them to new data</li></ul><p>
Collect initial data
</p>
<ul>
<li>• Describe field storage</li><li>• Describe field measurement level</li><li>• Import from various data formats</li><li>• Export to various data formats</li></ul><p>
Understand the data
</p>
<ul>
<li>• Audit the data</li><li>• Check for invalid values</li><li>• Take action for invalid values</li><li>• Define blanks</li></ul><p>
Set the unit of analysis
</p>
<ul>
<li>• Remove duplicates</li><li>• Aggregate data</li><li>• Transform nominal fields into flags</li><li>• Restructure data</li></ul><p>
Integrate data
</p>
<ul>
<li>• Append datasets</li><li>• Merge datasets</li><li>• Sample records</li></ul><p>
Transform fields
</p>
<ul>
<li>• Use the Control Language for Expression Manipulation</li><li>• Derive fields</li><li>• Reclassify fields</li><li>• Bin fields</li></ul><p>
Further field transformations
</p>
<ul>
<li>• Use functions</li><li>• Replace field values</li><li>• Transform distributions</li></ul><p>
Examine relationships
</p>
<ul>
<li>• Examine the relationship between two categorical fields</li><li>• Examine the relationship between a categorical and continuous field</li><li>• Examine the relationship between two continuous fields</li></ul><p>
Introduction to modeling
</p>
<ul>
<li>• Describe modeling objectives</li><li>• Create supervised models</li><li>• Create segmentation models</li></ul><p>
Improve efficiency
</p>
<ul>
<li>• Use database scalability by SQL pushback</li><li>• Process outliers and missing values with the Data Audit node</li><li>• Use the Set Globals node</li><li>• Use parameters</li><li>• Use looping and conditional execution</li></ul>- Knowledge of your business requirements- Data scientists
- Business analysts
- Clients who are new to IBM SPSS Modeler or want to find out more about using itIntroduction 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 executionIntroduction 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 execution2 jours1500.001890.00