This book introduces the fundamental elements of stochastic processes, covering basic concepts, core knowledge, and essential methods. It is organized into seven chapters, which include: the foundations of probability, concepts of stochastic processes, Poisson processes, discrete-time Markov chains, continuous-time Markov chains, simple Markovian queueing models, and stationary processes. Each chapter features figures, examples, exercises, and either solutions or guidance to support learning. Written from a non–measure-theoretic perspective, the book is accessible and highly readable, making it especially suitable for self-study.

The intended audience includes senior undergraduate and junior graduate students, as well as teachers in fields such as engineering, economics, management science, operations research, and applied mathematics. It also serves as a valuable reference for researchers and professionals with an interest in stochastic processes.