This course will examine the basic principles of probabilistic programming and Bayesian modelling, for analysis of data which may come from observational or experimental cognitive science studies. A variety of Bayesian data analysis will be discussed and implemented in an expressive probabilistic programming language. Approaches for model building, model checking and model validation will be discussed following a Bayesian workflow.