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, April 10-12, 2013 in San Antontio, TX.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.SyllabusDr. 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 diagnosticsclassificationclusteringmissing values imputationwhat-if scenario simulationtarget optimizationSpecial 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 5.1 Professional (the very latest release), so they can experiment with the full array of functions during and after the training.The class is limited to a maximum of ten 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 (see testimonials).Terms & Conditions The tuition fee for the 3-day course for commercial participants is US$ 2,995.Members of government agencies, the military and non-profit organizations are eligible for a reduced tuition fee of US$ 2,245 (≈25% discount).*Student and faculty of accredited academic institutions are eligible for a reduced tuition fee of US$ 1,495 (50% discount).*The course fee includes a Conference Pass for the BayesiaLab User Conference on October, 24, at the same venue as the course. A 60-day license to the full version of BayesiaLab Professional 5.1 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 or Mac OS X).The course fee includes all training materials, beverages, lunch and snacks during the training.Accommodation in San Antonio is at the participants' own expense, although negotiated rates are available at the seminar venue.*Proof of affiliation will be required upon registration. If you are not sure about your eligibility for reduced tuition fees, please email us at email@example.com.Testimonials from Earlier Courses"A must-take course for anyone looking to leverage advanced BBN techniques in virtually any domain." - Alex Cosmas, Booz Allen Hamilton"Attend, attend, attend! The training was well done allowing for both hands-on using BayesiaLab but also exploration of the Bayesian approach. Lionel was a great teacher – to have the brain behind the product guiding you was indeed amazing, no question went unanswered." - Yianna Vovides, The George Washington University"Bayesian Belief Networks is an advanced technique and Bayesia Lab makes such a complex technique easy to use on fingertips. Without any prior knowledge I had attended the Bayesia Lab Training in Chicago, April 2011 and found it very helpful & worth the money paid. The course structure / contents were well planned and by the end of the course I felt satisfied & had sense of mission accomplished. Dr. Jouffe has excellent teaching skills & in his training session there were several Q&A opportunities all addressed with a smiling face." - Senior Scientist at Fortune 500 CPG company"The Bayesia training session was one of the most valuable and thoughtful I have ever attended. Dr. Jouffe did an admirable job introducing and explaining Bayesian Belief Networks, an area of predictive modeling that is of rapidly increasing importance in many fields. The course adroitly mixed practical applications, case histories, and key concepts and theory, explaining the uses and remarkable power of these models. The approach was always informative and engaging, and included the best set of presentation materials I have encountered in a long time. This is a truly worthwhile course, and it also introduced a remarkable piece of analytical software. I speak as somebody who has given seminars and taught graduate courses for over twenty years; this session definitely deserves the highest praise." - Steven Struhl, Principal at SMS Research Analysis"I enjoyed the training course in Chicago in April 2011. It was very interesting and very well organized. I learned a lot of new things and I got inspired for applications of BayesiaLab in my daily job. Finally the environment: very friendly and productive with the other attendees coming both from business and academic world, a really wonderful “melting pot”. A very exiting experience which I recommend to all people interested in Bayesian networks." - Tommaso Pronunzio, Partner at Ales Market Research (Italy), ESOMAR Representative"I attended this training in Feb 2012 in Orlando. Dr. Jouffe did a great job explaining concepts of Bayesian Belief Networks. The hands-on sessions are extremely interesting. The BayesiaLab software has a lot of functions - you can do anything from correlation analysis to supervised learning algorithms! This tool can be for analysis in any area - ranging from market research to health care. I recommend this training to all people interested in Bayesian networks" - Krithika Bhuvaneshwar, Bioinformatician/Data Manager, Clinical Informatics, Lombardi Comprehensive Cancer Center, Georgetown University
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