United Arab Emirates University, Al-Ain, UAE
March 9–11, 2020, 9 a.m. to 5 p.m. (daily)
Take your BayesiaLab certification to the next level by joining the Advanced BayesiaLab course. This course gives you a broad view of what you can do with Bayesian networks. In the Advanced course, we study in more detail topics that are only quickly touched during the Introductory course:
Note that we also have much more hands-on exercises than during the Introductory course given that you are already familiar with all the basic concepts.
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 dialog between participants from a wide range of backgrounds.
Participants in the Advanced Course are required to have completed the Introductory Course on a previous date (see course calendar).
The traditional classroom setting remains the most popular option to take this course. The small group size ensures that you get plenty of opportunities to ask questions and get one-on-one coaching by the instructor.
If you are affiliated with a university, non-profit organization, or government agency, you may be eligible for special pricing as per the registration form below.
As an alternative to joining our classroom session in person, you can also participate via a simultaneous livestream from your home or office anywhere in the world.
If the timing of this course isn't right for you, you can always opt for a pre-recorded version of the advanced course. This allows you to start your own training program at your convenience.
Dr. Lionel Jouffe is co-founder and CEO of France-based Bayesia S.A.S. Lionel holds a Ph.D. in Computer Science from the University of Rennes and has been working in the field of Artificial Intelligence since the early 1990s. While working as a Professor/Researcher at ESIEA, Lionel started exploring the potential of Bayesian networks. After co-founding Bayesia in 2001, he and his team have been working full-time on the development BayesiaLab, which has since emerged as the leading software package for knowledge discovery, data mining and knowledge modeling using Bayesian networks. BayesiaLab enjoys broad acceptance in academic communities as well as in business and industry.
Applied researchers, statisticians, data scientists, data miners, decision scientists, biologists, ecologists, environmental scientists, epidemiologists, predictive modelers, econometricians, economists, market researchers, knowledge managers, marketing scientists, operations researchers, social scientists, students and teachers in related fields.
For a general overview of this field of study, we suggest that you download a free copy of our book, Bayesian Networks & BayesiaLab. Although by no means mandatory, reading its first three chapters would be an excellent preparation for the course.
"I would absolutely recommend this course as a thorough and in-depth introduction to Bayesian Networks and the BayesiaLab package. The small class sizes also contributed to an enjoyable and engaging learning experience."—Brian Potter, Infotools (Introductory Course in Melbourne, November 2015).
"This is one of the best
"Overall, this training was outstanding. Lionel is a gifted teacher, and it helps that you are showcasing a
“A must-take course for anyone looking to leverage advanced Bayesian network techniques in virtually any domain.”—Alex Cosmas, Chief Scientist, Booz Allen Hamilton (Introductory Course in Los Angeles, June 2011).
“The BayesiaLab software is impressive in its sophistication and multi-faceted abilities as a decision support tool. I had been using it primarily as a modeling tool for deductive analysis. Taking this class opened my eyes to BayesiaLab's incredible data-mining abilities. If you are looking for something that will provide a totally new angle on business decision problems, this is it!”—Michael Ryall,
"This class can only be described as eye-opening, the tool as terrific. Some of the best instruction for the shortest period of time I’ve ever received. A seriously terrific job.” —Beau Martin, President of American Choice Modeling (Introductory Course in Chicago, July 2013).