This course is an introduction to the probability models and stochastic processes (without measure theory) with the focus restricted to discrete time discrete state Markov chain and the applications to network science and data science. It also provides elementary numerical methods for solving real stochastic problems.

Note: To pass the course, apart from obtaining a minimum of 40% in the overall mark, a student must also obtain a minimum mark of 30% in both continuous assessment and examination components.