Level set methods, an important class of partial differential equation (PDE) methods, define dynamic surfaces implicitly as the level set (iso-surface) of a sampled, evolving nD function. This course is targeted for researchers interested in learning about the application of level set methods/models to visualization. The course material will be presented by recognized experts in the field, and will include extensive details on a variety of level set applications. The course will be taught at an intermediate level. Therefore attendees should have a working knowledge of calculus, linear algebra, computer graphics and geometric modeling. Some familiarity with differential geometry, differential equations, numerical computing and image processing is strongly recommended, but not required. The course will describe in detail level set methods for 3D morphing, contour-based surface reconstruction, a volume dataset segmentation framework, advanced segmentation techniques that utilize statistical shape models, piecewise smooth intensity models and ordered spatial dependencies. The course will close with a lecture on interactive segmentation with level set models on GPUs.