Getting Started with SAS Enterprise Miner for Machine Learning

Course Cover

5

(1)

compare button icon

Course Features

icon

Duration

2.33 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

2.33 hours

Course Description

This course introduces Enterprise Miner and demonstrates two common applications: segmentation, and predictive modeling. The course begins with an overview of Enterprise Miner and then moves on to segmentation and predictive modelling using a case study approach that is based on real-world data. Learners will be able to use Enterprise Miner to perform machine learning and data mining tasks after completing this course. Participants should have a solid quantitative background and, ideally, a basic understanding of predictive models including regression.

Jeffrey Thompson is a Senior Analyst Training Consultant at the SAS Institute. He has been working with SAS since the early 1990s. Jeffrey Thompson, a former associate professor of statistics at North Carolina State University has been published in the International Statistical Review and the Austrian Journal of Statistics among other peer-reviewed journals. He holds a bachelor's in mathematics, a masters in statistical computing and a doctorate in statistics.

Course Overview

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Learn how to use Enterprise Miner to perform data mining and machine learning tasks

Explore the fundamentals of predictive modeling and clustering

Discover how to build, compare, and deploy predictive models using SAS Enterprise Miner

Learn how to perform, interpret, and profile a cluster analysis using SAS Enterprise Miner

Course Instructors

Jeff Thompson

Instructor

Jeff Thompson is the instructor for this course
Course Cover