Course Description
Gaussian processes, stationary processes, Markov chain and Markov processes. Stochastic processes with independent increments, Brownian motions, martingales and semi-martingales.
Intended Learning Outcomes
CILO-1: Utilize the basic theory of Markov chains and martingales to solve problems in discrete time stochastic processes
CILO-2: Identify the key points for the convergence of Markov chains and martingales
CILO-3: Apply Markov chains and martingales to their own study in probability, statistics, and related fields