3-Day Introductory BayesiaLab Course in Chicago, IL
- Science & Technology
- Regus - John Hancock Tower, Chicago IL
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:
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.
Bayesia USA is the North American sales and consulting 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, Unilever, BBDO, GroupM, GfK, TNS, Ipsos, Mu Sigma, Booz Allen Hamilton, InterContinental Hotels Group, Dell and NASA's Jet Propulsion Laboratory among many others.
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