Lecture, three hours; computer laboratory, one hour. Requisite: course 14C or 30A, with grade of C- or better. Introduction to programming in Python and to machine learning and its many applications within chemical sciences. Topics include fundamentals of Python programming, routine numerical procedures such as optimization and linear regression, and overview of machine learning, with special emphasis on neural networks and deep learning, including implementation. Exploration of mainstream applications of machine learning to problems of chemical interest, including molecular simulation, protein structure prediction, and computer-aided drug and material design/discovery. Particular topics to be covered and projects to be completed may be decided in part based on student interest and input. P/NP or letter grading.