Introduction to Predictive Analytics with SPSS

Beginner SPSS Modeler Training

This course provides you with an overview of data mining and the fundamentals of using IBM SPSS Modeler. The principles and practice of data mining are illustrated using the CRISP-DM methodology. The course structure follows the stages of a typical data mining project, from reading data, to data exploration, data transformation, modeling, and effective interpretation of results. The course provides training in the basics of how to read, explore, and manipulate data with Modeller, and then create and use successful models.

  • icon for small classesSmall classes
  • icon for small classesComputer provided
  • icon for small classesBook included
  • icon for small classesFree retake

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Call for pricing 7 Hours PC provided 185 Madison Avenue, NYC In-person classroom training

Corporate & private training available

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What You'll Learn

  • Overview of data mining
  • Fundamentals of using SPSS Modeler
  • Modeling techniques
  • Evaluating and comparing model performance

Full Course Syllabus

Download PDF Outline

Introduction to data mining

The CRISP-DM methodology

Best practices for data mining

The basics of using IBM SPSS Modeler

Reading data files

Auditing and exploring data quality

Data manipulation

Searching for relationships among fields

Selecting data

Partitioning data for modeling

Modeling techniques in IBM SPSS Modeler

Creating models with decision trees

Evaluating and comparing model performance

Deploying and using models