Sports Predictive Analytics - Online Course at UCSD Extension - 10% Discount

DO NOT REGISTER ON MEETUP - USE CODE IEEEWI17 TO GET 10% DISCOUNT OFF THE $495 PRICE AND REGISTER AT http://extension.ucsd.edu/studyarea/index.cfm?vAction=singleCourse&vCourse=CSE-41245&CMP=EMC-DATA-IEEE (http://extension.ucsd.edu/studyarea/index.cfm?vAction=singleCourse&vCourse=CSE-41245&vsacategoryid=285&vStudyAreaID=103)

COURSE DATES 1/30/2017 - 3/19/2017.

Advancements in the field of predictive analytics have led to the creation of predictive models that can compute probabilities of sports win/loss prospects and analyze the performance of players. A well-known success story of sports predictive analytics is its role in predicting the performance of baseball players, which enabled the Boston Red Sox to win three World Series titles since 2004 after 86 years of losses.

In this course, students will compute simple statistics of a game which has already been played, then use correlation to detect statistical relationships between different game metrics. The science of rating and ranking will be covered in detail, and regression models will be used for estimating a metric from several predictor variables. Predictive models will then be used to compute win/loss probabilities.

Topics include:

Metrics used for team and player evaluationUse of sabermetrics for the evaluation of teamsTeam ranking using Massey, Colley and Elo methodsPredictive models for win/loss probabilitiesRegression techniques for machine learningFeature selection using Ridge and Lasso regressionSentiment analysis and its role in predicting the game outcomesPlayer and team performance report generation

Practical experience:

Apply predictive analytics to sports data to predict win/loss and other probabilities

Software: R (https://www.r-project.org/), a free software environment for statistical computing and graphics, is used for this course.

Course typically offered: Fall, Spring

Prerequisites: Introduction to Statistics (http://extension.ucsd.edu/studyarea/index.cfm?vAction=singleCourse&vCourse=CSE-41069) or equivalent knowledge recommended. Familiarity with R, SAS, SPSS, or similar statistical software recommended.

Course Number: CSE-41245 Credit: 2 units in Computer Science & Engineering

Ash Pahwa, Ph.D., is an educator, author, entrepreneur, and visionary with three decades of experience. He earned his doctorate in Comp. Sci. from Illinois Institute of Technology. He is listed in

Who's Who in the Frontiers of Science and Technology

. He is a Google Certified Analytics Consultant. His expertise is search engine optimization, web analytics and programming, digital image processing and video, DB management, and data storage technologies. He has worked for GE, AT&T Bell Labs, Xerox and Oracle. He founded A+ Web Services, CD-Gen, DV Studio Technologies. He wrote

CD-Recordable Bible

. He teaches at UCI, UCLA, UCSD and Chapman U.