The goal of my sessions are to help attendees "hit the ground running" by working through simple case studies with the MIT Uncertainty Quantification (MUQ) library. Those attending these sessions will be given interactive IPython notebooks to allow for hands-on experimentation. We will have one session on forward UQ, focused on Monte Carlo, polynomial chaos, and global sensitivities. The second session will focus on Bayesian Inference and the use of different MCMC algorithms for solving such problems. In both sessions, we will work through exercises to help build an intuitive understanding of our results. Attendees should bring a laptop but do not need to install any software; all examples will be provided through an easy-to-use web interface.