Information and Entropy
MIT's Information and Entropy examines the physical limits of communication and computation. The course covers digital signals, codes and compression, logic circuits, and computer architectures, alongside biological representations of information and algorithmic information theory. It applies the concept of entropy to channel capacity and to the second law of thermodynamics, and treats noise, probability, and error correction as central problems in reliable computing. Later sessions take up reversible and irreversible operations, the physics of computation, and an introduction to quantum computation. Materials come from MIT OpenCourseWare and include lecture notes, problem sets, and assignments used in the original MIT class, offered jointly through Electrical Engineering and Computer Science and Mechanical Engineering. No instructor video lectures are guaranteed, but the full set of course materials supports self-study of the subject from first principles to advanced applications.