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This lecture covers the generation of Markov processes, including discrete time/discrete space Markov chains, continuous time/discrete space Poisson processes, and the definition of Markov chains. It also discusses transition matrices, time homogeneity, stochastic matrices, and the properties of Markov chains. The lecture concludes with examples of Markov chains and transition kernels.