This lecture introduces Markov chains, a time-homogeneous stochastic process with values in a finite or countable set. It covers the definition, properties, transition matrix, and examples like a party and a simple symmetric random walk.
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The study of random walks finds many applications in computer science and communications. The goal of the course is to get familiar with the theory of random walks, and to get an overview of some appl
