Master predictive analytics with SAS Enterprise Miner and learn to turn raw data into decision-ready insights. You’ll begin by navigating the SAS workspace and configuring data sources, then progress through data exploration, variable selection, frequency tables, fit statistics, and transformations that improve model reliability and predictive accuracy.

As you advance, you’ll build and refine regression, decision tree, neural network, and ensemble models. You’ll interpret diagnostic plots, tree structures, neural network weights, ROC charts, iteration plots, and lift charts, then compare model performance using ASE and event-based overlays. You’ll also use Auto Neural and Dmine Regression, construct flow diagrams, and document workflows that support model deployment and business decision-making. Designed for learners pursuing predictive analytics roles or applying modeling in finance, healthcare, and marketing, this course combines foundational concepts with structured practice, graded quizzes, interactive analysis, and real-world case scenarios. Its step-by-step progression helps you confidently prepare data, evaluate competing models, select the strongest performer, and deploy predictive analytics workflows. Enroll to develop practical SAS modeling skills for real-world business applications.