The purpose of this course is to get students up-to-speed regarding the practice of modern Bayesian econometrics. The semester-long course is divided into two modules, with the first module serving as an introduction to basic Bayesian theory. The second module illustrates the use of MCMC methods in a wide array of (mostly microeconometric) models. During the second module in particular, students will be responsible for programming posterior simulators using real and artificial data.