Stochastic Processes

This course introduces students to the fundamental concepts of stochastic processes, particularly Markov chains, and related structures. These time-dependent probabilistic models are essential for modelling many real-world systems, be it a telecommunications network, a hospital waiting list or a transport system. They also arise in many other environments, where you wish to capture the development of some element of random behaviour over time, such as the state of a game or a decision process. Stochastic processes also form the basis of many advanced numerical methods in applied mathematics and machine learning.