2-day course: Fundamentals of Bayesian Inference using Probabilistic Programming
Welcome to the world of probabilistic programming and Bayesian inference!
In this short course/tutorial (2 x 3h) you will learn the fundamentals of Bayesian inference using a rather new paradigm called probabilistic programming. No prior knowledge of Bayesian theory is necessary.
You will learn about the basic intuitions behind popular inference algorithms as well as how to design and write small models / probabilistic programs in popular probabilistic programming languages (for instance WebPPL and Stan).
The tutorial will be highly interactive, where the course participants perform experiments using their own computers. We also recommend that you participate onsite (if possible) to make the interactive experience as good as possible, but we will also provide an option to participate online.
Course dates: 1 June 14.00-17.00 and 7 June 14.00-17.00 CEST (UTC+2)
Course lecturer: Assoc. Prof. David Broman, KTH and Digital Futures
For questions please contact: David Broman, email@example.com
This course is a collaboration between TECoSA and Digital Futures.