(Formerly numbered 125.) Lecture, three hours; computer laboratory, one hour. Requisite: course 14C or 30A, with grade of C- or better. Comprehensive introduction to machine learning (ML) algorithms and their applications in the field of chemistry and biochemistry. Study is designed to provide students with both the theoretical understanding of ML algorithms and the practical skills needed to apply these techniques to solve real-world problems in chemistry. Through lectures, hands-on laboratories, and project work, students learn to analyze chemical datasets, predict chemical properties, and develop models for chemical behavior using ML. Concurrently scheduled with course C225. P/NP or letter grading.