Stan is an open-source, Bayesian inference tool with interfaces in R, Python, Matlab, Julia, Stata, and the command line. Users write statistical models in a high-level statistical language. The default Bayesian inference algorithm is the no-U-turn sampler (NUTS), an auto-tuned version of Hamiltonian Monte Carlo. Stan was developed to address the speed and scalability issues of existing Bayesian inference tools. The goal of the workshop is the practical application of Stan to different models starting with ordinary linear regression and ending with more complex models such as generalized linear mixed and hierarchical models.