This is a first graduate course on measure theoretic probability with applications. Topics include: probability spaces, random variables, expectations in terms of the theory of measure and integration, modes of convergence, limit theorems for independent random variables, Radon-Nikodym theorem, conditional expectations, Martingales. Applications to Markov chains.