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Data Mining & Predictive Analytics Essentials

About This Course

For years, high-end computer systems have relied on sophisticated data mining techniques to detect credit card fraud, predict weather patterns, recommend online content, assist in solving crimes, and guide business decisions. Recent innovations in machine learning, statistics and programming have made these tools more accurate, easier to use and more widely available.

In this course, you’ll become fluent in data mining and get an introduction to the latest predictive analytics technologies. You’ll learn key techniques and gain hands-on experience using modern tools, code libraries and programming resources to analyze large datasets. You’ll also practice applying machine learning to generate predictions and actionable recommendations that can enhance business performance and strategic decision-making.

What You’ll Learn

  • Essential data mining and machine learning concepts

  • Regression, cluster, classification and decision tree analysis methods

  • Unsupervised and supervised learning models

  • Advanced R programming skills

Get Hands-On Experience

  • Use powerful desktop and web-based analytics tools

  • Complete data mining and predictive analytics projects by writing R code using tidyverse, caret, cluster and other packages

Course Sessions

Online Synchronous

January 2027
Dates Jan 11 - Mar 29
Location Online
Instructor R. Sean Bethune
Cost $1,615
Scheduled Meetings
Date
Day
Time
Location
Jan 11, 2027
Mon
6 – 9 p.m.
Online
Jan 25, 2027
Mon
6 – 9 p.m.
Online
Feb 1, 2027
Mon
6 – 9 p.m.
Online
Feb 8, 2027
Mon
6 – 9 p.m.
Online
Feb 22, 2027
Mon
6 – 9 p.m.
Online
Mar 1, 2027
Mon
6 – 9 p.m.
Online
Mar 8, 2027
Mon
6 – 9 p.m.
Online
Mar 15, 2027
Mon
6 – 9 p.m.
Online
Mar 22, 2027
Mon
6 – 9 p.m.
Online
Mar 29, 2027
Mon
6 – 9 p.m.
Online

All times are Pacific Time.

Noncredit Course

You'll earn 3.0 continuing education units (CEUs) for successfully completing this course.