Stochastic Models for Communications: Introduction

This lecture introduces mathematical and theoretical tools for stochastic processes relevant to communication systems and data science, focusing on engineers. Topics include random variables, continuous and discrete-time stochastic processes, Poisson processes, Markov chains, and queuing theory. The course aims to prepare students for advanced courses in digital communications, information theory, signal processing, and more. Prerequisites include linear algebra, analysis, probability, and signal processing. The organization includes live Zoom sessions, pre-recorded blackboard lectures, and exercise sessions with a focus on student participation and problem-solving.