IBM SPSS Modeler Foundations (v18.2) Course Details:

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.

    Nov 15 2021

    Date: 11/15/2021 - 11/16/2021 (Monday - Tuesday) | 9:00 AM - 5:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    IBM SPSS Modeler Foundations (v18.2)

    November 15 - 16, 2021 | 9:00 AM - 5:00 PM (EST) | Virtual Classroom Live


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    Dec 6 2021

    Date: 12/06/2021 - 12/07/2021 (Monday - Tuesday) | 9:00 AM - 5:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    IBM SPSS Modeler Foundations (v18.2)

    December 6 - 7, 2021 | 9:00 AM - 5:00 PM (EST) | Virtual Classroom Live


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    Dec 27 2021

    Date: 12/27/2021 - 12/28/2021 (Monday - Tuesday) | 9:00 AM - 5:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    IBM SPSS Modeler Foundations (v18.2)

    December 27 - 28, 2021 | 9:00 AM - 5:00 PM (EST) | Virtual Classroom Live


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    Jan 17 2022

    Date: 01/17/2022 - 01/18/2022 (Monday - Tuesday) | 9:00 AM - 5:00 PM (EST)
    Location: ONLINE (Virtual Classroom Live)
    Delivery Format: VIRTUAL CLASSROOM LIVE Request Quote & Enroll

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    IBM SPSS Modeler Foundations (v18.2)

    January 17 - 18, 2022 | 9:00 AM - 5:00 PM (EST) | Virtual Classroom Live


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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

*Please Note: Course Outline is subject to change without notice. Exact course outline will be provided at time of registration.
  • Collect initial data
  • Understand the data
  • Set the unit of analysis
  • Integrate data
  • Transform fields
  • Further field transformations
  • Examine relationships
  • Introduction to modeling
  • Improve efficiency

 

Understand your business requirements. 

  • Business Analysts
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