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IBM SPSS Modeler Foundations (V18.2)

  • Kursuskode 0A069G
  • Varighed 2 dage

Åbent kursus Pris

DKR10.270,00

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Beskrivelse

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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.

Kursusdato

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    • Leveringsmetode: Åbent kursus (Virtuelt)
    • Dato: 31 oktober-01 november, 2024
    • Kursussted: Virtual
    • Sprog: engelsk

    DKR10.270,00

Målgruppe

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

Kursets formål

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Please refer to course overview.

Kursusindhold

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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

Forudsætninger

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  • Knowledge of your business requirements
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