Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes. The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.

Introduction to Solid State Chemistry is a one-semester college course on the principles of chemistry. This unique and popular course satisfies MIT's general chemistry degree requirement, with an emphasis on solid-state materials and their application to engineering systems. You'll begin with an exploration of the fundamental relationship between electronic structure, chemical bonding, and atomic order, then proceed to the chemical properties of "aggregates of molecules," including crystals, metals, glasses, semiconductors, solutions and acid-base equilibria, polymers, and biomaterials. Real-world examples are drawn from industrial practice (e.g. semiconductor manufacturing), energy generation and storage (e.g. automobile engines, lithium batteries), emerging technologies (e.g. photonic and biomedical devices), and the environmental impact of chemical processing (e.g. recycling glass, metal, and plastic).