Advanced topics in time series modelling and forecasting in a reading/seminar-style format. Topics include dynamic state-space models and their applications, Bayesian learning and forecasting, statistical model developments motivated by forecasting applications in many fields, and advanced topics interfacing with current research frontiers. Instructor consent required. Prerequisite: Statistical Science 732 and 831. Recommended prerequisite: Statistical Science 642.