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EncartaLabs

IBM SPSS Modeler - Foundations

( Duration: 2 Days )

The IBM SPSS Modeler - Foundations training course, provides the foundations of using IBM SPSS Modeler and introduces you to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides skills on the basics of how to import, explore, and prepare data with IBM SPSS Modeler, and introduces you to modeling.

The IBM SPSS Modeler - Foundations workshop is designed for Data scientists, Business analysts and those who are new to IBM SPSS Modeler or want to find out more about using it.

COURSE AGENDA

1

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
2

Collect initial data

  • Describe field storage
  • Describe field measurement level
  • Import from various data formats
  • Export to various data formats
3

Understand the data

  • Audit the data
  • Check for invalid values
  • Take action for invalid values
  • Define blanks
4

Set the unit of analysis

  • Remove duplicates
  • Aggregate data
  • Transform nominal fields into flags
  • Restructure data
5

Integrate data

  • Append datasets
  • Merge datasets
  • Sample records
6

Transform fields

  • Use the Control Language for Expression Manipulation
  • Derive fields
  • Reclassify fields
  • Bin fields
7

Further field transformations

  • Use functions
  • Replace field values
  • Transform distributions
8

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
9

Introduction to modeling

  • Describe modeling objectives
  • Create supervised models
  • Create segmentation models
10

Further field transformations

  • Use functions
  • Replace field values
  • Transform distributions
11

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

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  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting https://www.encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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