This short-course on the Verification and Validation (V&V) of computational models teaches techniques to quantify prediction uncertainty which includes the broad classes of, first, numerical uncertainty caused by truncation effects in the discretization of partial differential equations and, second, parametric uncertainty caused by the variability of model parameters. It focuses on applications in structural mechanics and structural dynamics. The quantification includes the propagation and assessment of how much uncertainty is present in the simulation of an application of interest (“what are the sources, how much uncertainty is present?”). It includes understanding which effects control the uncertainty (“is it predominantly the mesh discretization, parameter variability, or other phenomena?”) and what can be done to reduce the overall uncertainty (“should the mesh be refined, should small-scale experiments be performed, should model parameters be calibrated and how?”). A more detailed course summary can be found in the link below.