Introduction to Stochastic Processes
MIT OpenCourseWare's graduate-level introduction to stochastic processes covers Markov chains, random walks, martingales, and the Galton-Watson branching tree. The course assumes prior grounding in probability theory and linear algebra, including conditional expectation and matrix operations. Materials include lecture notes, problem sets, and exams drawn from MIT's Mathematics Department curriculum, following the standard OCW format of self-study readings and assignments without live instruction. Topics build from basic chain theory toward more advanced tools used in modeling random systems that evolve over time, useful preparation for further work in probability, statistics, or applied mathematics. As with other MIT OCW offerings, all course materials are free to access and there is no certificate offered.