Three-Day Advanced Course:
Artificial Intelligence with Bayesian Networks & BayesiaLab
University of Phoenix, 203 N. LaSalle St, Classroom 1344, Chicago, IL 60601
November 5–7, 2018, 9 a.m.–5 p.m. (daily)
Please not that this course takes place at an offsite venue, not at the BayesiaLab Conference hotel.
Take your BayesiaLab certification to the next level by joining the advanced BayesiaLab course. Completing this course brings you to the leading edge of applied research with Bayesian networks. Dr. Lionel Jouffe, CEO of Bayesia, will teach this three-day course.
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).
- Manual Modeling with BEKEE
- Probability Table Analysis
- Parameter Sensitivity Analysis
- Function Nodes
- Influence Diagrams
- Dynamic Bayesian Networks
- Bayesian Updating
- Discretization of the Continuous Variables
- Aggregation of the Discrete States
- Missing Values Processing
- Synthesis of New Variables (Manual Synthesis and Data Clustering)
- Fine-Tuning of Learning Algorithms
- Evidence Analysis
- Target Optimization
- Contribution Analysis
- Negative and Disjunctive Inference
- Evidence Instantiation and Evidence Data Weighting
Terms & Conditions
- You may cancel your registration for a full refund of the course fees up to 30 days before the start of the course. If you cancel within 30 days of the event, your course fee will not be refunded. However, you will be able to apply 100% of the paid course fees towards future BayesiaLab courses.
- A 90-day license to the full version of BayesiaLab Professional Edition will be provided to all participants for installation on their computers prior to the event.
- Participants will be required to bring their own WiFi-enabled computer/laptop to the seminar (Windows XP, Vista, 7, 8, 10 or Mac OS X).
- The course fee includes all training materials.
- Accommodation is at the participants' own expense.
"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).