Course Overview

This course will show you how to use IBM SPSS Modeler to automate the building of predictive models. The course will show you how to build predictive models for customer behavior and build customer segmentation using various cluster models. You will learn how to read data from various sources and automatically prepare data for modeling using a variety of methods. Scoring new data using the model will also be discussed.

Who Should Attend

This basic course is for anyone with little or no experience using IBM SPSS Modeler (formerly Clementine) or with data mining in general.

Course Certifications

This course is part of the following Certifications:

Prerequisites

  • General computer literacy.
It would be helpful if you had:
  • an understanding of your organization’s data, as well as any of your organization’s business issues that are relevant to the use of data mining.
No statistical background is necessary.

Course Content

  • Introduction to data mining
  • The CRISP-DM methodology
  • Best practices for data mining
  • The basics of using IBM SPSS Modeler
  • Reading data files
  • Working with dates
  • Auditing and exploring data quality
  • Searching for anomalous data and outliers
  • Data manipulation
  • Searching for relationships among fields
  • Combining data files by appending and/or merging
  • Restructuring data files with aggregate
  • Sampling data
  • Partitioning data for modeling
  • Modeling techniques in IBM SPSS Modeler
  • Automatic Modeling for Binary Outcomes
  • Evaluating and comparing model performance
  • Deploying and using models
  • Running IBM SPSS Statistics commands from IBM SPSS Modeler