Discrete Stochastic Processes
MIT OpenCourseWare's graduate course on probabilistic systems that evolve through random changes at discrete time steps. Topics include Markov chains, renewal processes, Markov reward and decision theory, and an introduction to countable-state Markov chains and their steady-state behavior. The course builds both the mathematical machinery and the intuition needed to model systems that appear in engineering, physics, biology, operations research, and finance. Materials include full lecture notes, problem sets with solutions, and exams, following MIT's standard OCW format for advanced coursework. No instructor video lectures are included, but the written materials are detailed enough to work through independently. The course assumes prior exposure to probability theory and is pitched at graduate or advanced undergraduate level. All content is free to access and download under MIT's open license, with no certificate offered.