Overview

Highly successful businesses know that the rules have changed. No longer can they rely solely on their product or service to grow; they must leverage their data (financial, customer support, web interactions, etc.) to better understand their customers and learn from the collective experiences of their organizations to remain competitive. Predictive Analytics provides clear, actionable initiatives based on existing company data and is a natural extension of related corporate initiatives in areas such as web analytics, business analysis, and data mining. As Eric Siegel, Ph.D., chairman of the Predictive Analytics World often quotes, “Business is becoming a numbers game and Predictive Analytics is the way to play it.”

In his bestselling book, Moneyball, Michael Lewis demonstrates the power of Predictive Analytics as he tells the story of the Oakland A’s manager, Billy Beane (made famous by his portrayal by Brad Pitt in Colombia Picture’s hit film). Beane, who was constrained with the lowest team budget in Major League Baseball, used Predictive Analytics techniques to orchestrate a dramatic turnaround in his team’s performance.

UC Irvine Extension’s Predictive Analytics certificate is a comprehensive online program designed for working adults within a wide range of professional backgrounds to develop the skills they need to succeed in this exciting, high growth field. Learn how to better understand customer needs and business processes in ways that drive business results. Optimize your marketing campaigns and website behavior to increase customer responses and conversions.

Who Should Attend

This program is intended for professionals who are using or wish to use Predictive Analytics to optimize business performance at a variety of levels in a wide range of industries. The Predictive Analytics program is often the logical next step for professional growth for those in business analysis, web analytics, marketing, business intelligence, data warehousing, and data mining.

Certificate Candidacy

The program is open to working adults within a wide range of professional backgrounds. An Application for Candidacy must be submitted before the completion of the third course in the program.

Certificate Requirements

The Predictive Analytics Certificate is awarded upon the minimum completion of five (5) Required Courses and (3) Elective Courses totaling eight (8) courses for a minimum of sixteen (16) units or 160 hours of instruction with a grade point average of ‘C’ or better.

On-site Training Available

Through Corporate Training, we can deliver this program or customize one that fits your organization's specific needs. Visit Corporate Training or call (949) 824-1847 for information.

English Proficiency Requirement
All certificate programs at UC Irvine Extension (classroom and online formats) require professional-level English language proficiency in listening and note-taking, reading comprehension and vocabulary, written expression, and oral presentation. If you would like to refine your English language proficiency prior to beginning one of our programs, please see our English Language Programs.

Stay Informed About
Predictive Analytics

Presented in partnership with:

Predictive Analytics World is the business-focused event for predictive analytics professionals, managers and commercial practitioners.

Predictive Analytics Special Topic Webinar: The Power to Predict Who Will Click, Buy, Lie, or Die
Recorded 2/19/2013
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Predictive Analytics Special Topic Webinar: Text Analytics & Text Mining
Recorded 1/15/2013
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Predictive Analytics Educational Planning Session
Recorded 12/20/2012
View Webinar

Program Benefits

• Understand the art and science of Predictive Analytics to define clear actions that result in improved decisions and business results
• Develop actionable plans from existing corporate data and initiatives to increase sales, reduce marketing costs, and improve customer retention
• Select, prepare, construct, integrate, structure, and format data to be most effective to ensure the predictive model meets the business goals
• Learn how to suppress those customers least likely to respond to direct marketing campaigns
• Define appropriate business goals for a predictive analytics implementation in the “language” of a specific industry or business
• Optimize product development, manufacturing, testing, and maintenance
• Understand the use and assist in the selection of industry standard analytics tools
• Integrate powerful and traditionally untapped sources of information including social data, unstructured text and Big Data sets
• Manage fraud by scoring and ranking data collected from interaction with customers

Advisory Committee

• Dean Abbott, President, Abbott Analytics
• John Elder, Ph.D., Chief Scientist, Elder Research
• Ian Harris, Ph.D., Associate Professor, Department of Computer Science, The Bren School of Information and Computer Science, University of California, Irvine
• Gary Miner, Ph.D., Senior Consultant/Statistician, Statsoft
• Bob Nisbet, Ph.D., Consulting Data Scientist
• Eric Siegel, Ph.D., Chair, Predictive Analytics World
• Padhraic Smyth, Ph.D., Professor, Department of Computer Science, The Bren School of Information and Computer Science, University of California, Irvine
• Jim Sterne, President, Target Marketing; Chairman, Digital Analytics Association, Founder, eMetrics Marketing Optimization Summit
• James Taylor, CEO, Decision Management Solutions