Science - Course - Applied Probability Models

The main aims of this course are to provide a thorough account of basic probability theory; to introduce the ideas and tools of the theory of stochastic processes; to discuss in depth important classes of stochastic processes, including Markov Chains (both in discrete and continuous time), Poisson processes, the Brownian motion and Martingales. The course will also cover other important but less routine topics, like Markov decision processes and some elements of queueing theory. Pre-requisite: MATH 242.