Markov Chains: Theory and Applications

This lecture introduces the concept of Markov chains, focusing on discrete-time Markov chains and their applications in modeling time-dependent random phenomena, decision-making under uncertainty, and optimal control models. The lecture covers the prerequisites, general remarks, recommended books, and the course outline. It also discusses the tools used in business analytics, such as Markov chain models and Markov decision processes, highlighting their applications in various fields like marketing, finance, and supply chain management.