EncartaLabs

IBM SPSS Modeler - Data Science

( Duration: 2 Days )

This IBM SPSS Modeler - Data Science course provides the fundamentals of using IBM SPSS Modeler and introduces the attendee 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, and introduces the attendee to modeling.

By attending IBM SPSS Modeler - Data Science workshop, attendees will learn:

  • Introduction to data science
  • Introduction to IBM SPSS Modeler
  • Introduction to data science using IBM SPSS Modeler
  • Collecting initial data
  • Understanding the data
  • Setting the of analysis
  • Integrating data
  • Deriving and reclassifying fields
  • Identifying relationships
  • Introduction to modeling

  • Understanding of your business data
  • Business analysts
  • Data scientists

COURSE AGENDA

1

Introduction to data science

  • List two applications of data science
  • Explain the stages in the CRISP-DM methodology
  • Describe the skills needed for data science
2

Introduction to IBM SPSS Modeler

  • Describe IBM SPSS Modeler's user-interface
  • Work with nodes and streams
  • Generate nodes from output
  • Use SuperNodes
  • Execute streams
  • Open and save streams
  • Use Help
3

Introduction to data science using IBM SPSS Modeler

  • Explain the basic framework of a data-science project
  • Build a model
  • Deploy a model
4

Collecting initial data

  • Explain the concepts 'data structure', 'of analysis', 'field storage' and 'field measurement level'
  • Import Microsoft Excel files
  • Import IBM SPSS Statistics files
  • Import text files
  • Import from databases
  • Export data to various formats
5

Understanding the data

  • Audit the data
  • Check for invalid values
  • Take action for invalid values
  • Define blanks
6

Setting the of analysis

  • Remove duplicate records
  • Aggregate records
  • Expand a categorical field into a series of flag fields
  • Transpose data
7

Integrating data

  • Append records from multiple datasets
  • Merge fields from multiple datasets
  • Sample records
8

Deriving and reclassifying fields

  • Use the Control Language for Expression Manipulation (CLEM)
  • Derive new fields
  • Reclassify field values
9

Identifying relationships

  • Examine the relationship between two categorical fields
  • Examine the relationship between a categorical field and a continuous field
  • Examine the relationship between two continuous fields
10

Introduction to modeling

  • List three types of models
  • Use a supervised model
  • Use a segmentation model

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://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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