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IBM SPSS Modeler Foundations (V18.2)

  • Code training 0A069G
  • Duur 2 dagen
  • Taal Engels

Klassikale training Prijs

eur1.500,00

(excl. BTW)

Vraag een groepstraining aan Schrijf je in

Methode

Deze training is in de volgende formats beschikbaar:

  • Class Connect

    Verbind naar een klas in HD

  • E-learning (in je eigen tempo)

    Elektronisch leren in je eigen tempo

  • Klassikale training

    Klassikaal leren

  • Op locatie klant

    Op locatie klant

  • Virtueel leren

    Virtueel leren

Vraag deze training aan in een andere lesvorm.

Trainingsbeschrijving

Naar boven

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.

    • Methode: Virtueel leren
    • Datum: 31 oktober-01 november, 2024
    • Locatie: Virtueel-en-klassikaal
    • Taal: Engels

    eur1.500,00

Doelgroep

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

Trainingsdoelstellingen

Naar boven

Course covers an introduction to IBM SPSS Modeler 

Inhoud training

Naar boven
  • 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

Voorkennis

Naar boven
  • Knowledge of your business requirements
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