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IBM SPSS Modeler: Getting Started
Rating: 4.5 out of 5(426 ratings)
1,570 students

IBM SPSS Modeler: Getting Started

Learn how to do Data Mining using IBM SPSS Modeler.
Created bySandy Midili
Last updated 5/2014
English

What you'll learn

  • Data Mining and Advanced Analytics Defined
  • Modeling Methods in Modeler
  • CRISP-DM Overview
  • General Modeler Orientation
  • Reading Data
  • Assessing Data Quality
  • Integrating Data
  • Constructing Data
  • Modeling
  • Evaluation
  • Deployment

Course content

6 sections22 lectures4h 9m total length
  • What is Advanced Analytics and Data Mining?18:39

    Define data mining, advanced analytics, and prescriptive analytics using IBM SPSS Modeler to build predictive models and deploy them on historical data.

  • Modeling Methods25:46
  • What is CRISP-DM?8:53
  • Modeler's Workbench Design6:49
  • General Modeler Orientation22:04

Requirements

  • This course is for anyone that would like to learn how to use IBM SPSS Modeler.
  • This course is for anyone that would like to learn how to do Data Mining.
  • No statistical or data mining background is necessary.

Description

IBM SPSS Modeler is a data mining workbench that helps you build predictive models quickly and intuitively, without programming. Analysts typically use SPSS Modeler to analyze data by doing data mining and then deploying models.

Overview: This course introduces students to data mining and to the functionality available within IBM SPSS Modeler. The series of stand-alone videos, are designed to introduce students to specific nodes or data mining topics. Each video consists of detailed instructions explaining why we are using a technique, in what situations it is used, how to set it up, and how to interpret the results. This course is broken up into phases. The Introduction to Data Mining Phase is designed to get you up to speed on the idea of data mining. You will also learn about the CRISP-DM methodology which will serve as a guide throughout the course and you will also learn how to navigate within Modeler. The Data Understanding Phase addresses the need to understand what your data resources are and the characteristics of those resources. We will discuss how to read data into Modeler. We will also focus on describing, exploring, and assessing data quality. The Data Preparation Phase discusses how to integrate and construct data. While the Modeling Phase will focus on building a predictive model. The Evaluation Phase focuses how to take your data mining results so that you can achieve your business objectives. And finally the Deployment Phase allows you to do something with your findings.

Who this course is for:

  • This course is for anyone that would like to learn how to use IBM SPSS Modeler.
  • This course is for anyone that would like to learn how to do Data Mining.