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3-Day Introductory BayesiaLab Course in Los Angeles, CA


Tuesday, September 16, 2014 at 9:00 AM - Thursday, September 18, 2014 at 5:00 PM (PDT)

3-Day Introductory BayesiaLab Course in Los Angeles, CA

Ticket Information

Ticket Type Sales End Price Fee Quantity
3-Day Introductory BayesiaLab Course (Commercial Tuition)   more info Ended $2,995.00 $0.00
3-Day Introductory BayesiaLab Course (Reduced Tuition for Gov't/Non-Profits)   more info Ended $2,245.00 $0.00
3-Day Introductory BayesiaLab Course (Reduced Tuition for Students/Faculty)   more info Ended $1,495.00 $0.00

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Event Details

Learn the foundations of Probabilistic Graphical Models & Bayesian Networks and how to use them as a practical research framework with the BayesiaLab software platform. Join us for this 3-day course, September 16-18, 2014 in Los Angeles.

Audience: Applied researchers, statisticians, data scientists, data miners, epidemiologists, predictive modelers, econometricians, economists, market researchers, knowledge managers, marketing scientists, students and teachers in related fields.

Level: The course will be taught at a beginner level, so no prior knowledge of Bayesian networks is necessary. However, undergraduate-level familiarity with probability theory and statistics is recommended.

Objective: Completing the course as a Certified BayesiaLab Analyst and becoming proficient in using Bayesian networks for a broad range of applied research and analytics tasks.


Dr. Lionel Jouffe, who is one of the world's foremost experts on Bayesian networks, will host this 3-day seminar and teach his proven curriculum. The course covers the basics of probabilistic graphical models and introduces BayesiaLab as the software platform for manually modeling and machine-learning Bayesian networks. Participants will learn how to generate Bayesian networks for a wide range of analytics tasks, including:

  • prediction/forecasting 
  • diagnostics
  • classification
  • clustering
  • missing values imputation
  • what-if scenario simulation
  • target optimization

Special emphasis will be given to observational versus causal inference, which is particularly relevant in the context of Big Data. Course topics are presented in alternating sessions of lectures and exercises, with ample opportunity for Q&A.

In conjunction with the seminar, participants will have access to an unrestricted 60-day license of BayesiaLab 5.3 Professional so they can experiment with the full array of functions during and after the training.

The class is limited to a maximum of 15 participants in order to allow for one-on-one coaching during the hands-on exercises with BayesiaLab. This small-group format provides a productive yet informal learning environment that facilitates a lively dialogue between participants from a wide range of backgrounds.

Have questions about 3-Day Introductory BayesiaLab Course in Los Angeles, CA? Contact Bayesia

When & Where

Carnesale Commons
251 Charles E Young Dr West
Los Angeles, CA 90095

Tuesday, September 16, 2014 at 9:00 AM - Thursday, September 18, 2014 at 5:00 PM (PDT)

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Bayesia USA is the North American sales and marketing organization for France-based Bayesia S.A.S. Their mission is to promote Bayesian networks as a new framework for knowledge discovery and reasoning within complex domains.

Founded by two professors in the field of artificial intelligence in 2001 and headquartered in northwestern France, Bayesia S.A.S. is the world's leading developer of research software based on the Bayesian network paradigm. Their principal product, BayesiaLab, is the only software platform that can perform unsupervised structural learning for knowledge discovery.

Today, BayesiaLab is being used by researchers in major organizations around the world, including P&G, Microsoft, Intel, GlaxoSmithKline, Booz Allen Hamilton, Hyatt Hotels Corporation, GfK, TNS, Ipsos, Nielsen, the Federal Aviation Administration, the U.S. Army, the U.S. EPA, and the U.S. Veterans Administration among many others.

GfK, TNS, Ipsos, 

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3-Day Introductory BayesiaLab Course in Los Angeles, CA
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