This course is an advanced introduction to uncertainty propagation and quantification in model-based simulations. Examples are drawn from a variety of engineering and science applications, emphasizing systems governed by ordinary or partial differential equations. The course will emphasize a probabilitic framework and will survey classical and modern approaches, including sampling methods and techniques based on functional approximations.