This module aims to present some advanced probabilistic concepts and techniques, and demonstrate their application to stochastic modelling of real-world situations. The topics covered include random walks, renewal theory, Poisson process, continuous-time Markov processes and Brownian motion. In addition to exposure to proofs and theoretical material, students develop practical skills through a large number of problems and worked examples.