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authorKurt Schulzke, Associate Professor of Accounting & Law, University of North Georgia Introductory Course, Washington 2019

This is an exceptional three-day intro to Bayesian networks led by top-drawer faculty. Creating a full-dress structural equation model (SEM) in an hour sounds crazy. Because it's impossible. But not with BayesiaLab's probabilistic structural equation model (PSEM) workflow. If you're in data science and haven't experienced BayesiaLab, it's high time. Peerless supervised and unsupervised learning. BayesiaLab beats the stuffing out of traditional linear and logistic regression. No data? No problem -- use expert elicitation to build, validate and optimize your model. Three days just scratches the surface on this powerful analytical tool.

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authorLisa Shaffer, Marketing Science Specialist at RTi Research, Introductory Course, NYC 2019

The BayesiaLab training course covers it all, from probability theory to practical examples of how to use the wide range of features that the program offers. The hands-on learning sessions help to answer not only how to create and use Bayesian networks, but why doing so is a breakthrough approach in virtually any field. Lionel is a great instructor who is always listening to feedback in order to make both the course and BayesiaLab itself the best it can be.

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authorBill Anderson, Software Engineering Institute, Carnegie Mellon University, Introductory Course, NYC 2019

Bring your raincoat to be ready for a firehose of amazing content!!