Learn How To:

• define a SAS Enterprise Miner project and explore data graphically
• modify data for better analysis results
• build and understand predictive models such as decision trees and regression models
• compare and explain complex models
• generate and use score code
• apply association and sequence discovery to transaction data.

Who should attend?

• Data analysts
• Aualitative experts, and others who want an introduction to SAS Enterprise Miner

Prerequisites:

• Before attending this course, you should be acquainted with Microsoft Windows and Windows software.
• In addition, you should have at least an introductory-level familiarity with basic statistics and regression modeling.
• Previous SAS software experience is helpful but not required.
• This course addresses SAS Enterprise Miner software.

Course Outline:

• Introduction
• Accessing and Assaying Prepared Data
• Introduction to Predictive Modeling: Predictive Modeling Fundamentals and Decision Trees
• Introduction to Predictive Modeling: Regressions
• Introduction to Predictive Modeling: Neural Networks and Other Modeling Tools
• Model Assessment
• Model Implementation
• Introduction to Pattern Discovery
• Special Topics
• Case Studies

The fees is inclusive of:

• Training & Digital Badge.
• Course material.
• 2 attempts of Global certification.