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Schulung - IBM 0A069G - IBM SPSS Modeler Foundations (V18.2)

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DURCHFÜHRUNG MIT TERMIN
Dauer
2 Tage (16 Stunden)
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1.600,00 € netto
1.904,00 € inkl. 19% MwSt.
Nr.
30375
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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.

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Zielgruppe

Wer sollte teilnehmen:

Zielgruppe

Audience

  • Data scientists
  • Business analysts
  • Clients who are new to IBM SPSS Modeler or want to find out more about using it

Voraussetzungen

Prerequisites

  • Knowledge of your business requirements
Trainingsprogramm

Trainingsprogramm

Course Outline

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

Objective

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
Schulungsmethode

Schulungsmethode

presentation, discussion, hands-on exercises

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    Schulung - IBM 0A069G - IBM SPSS Modeler Foundations (V18.2)