Lecture, four hours; discussion, two hours. Requisite: course 200 or equivalent. Introduction to machine learning analysis of biomedical data, with focus on formulating interdisciplinary problems as computational problems and then solving those problems using machine learning techniques and computational interdisciplinary research in genetics. Fundamentals of machine learning and applications to genetics and health records. Letter grading.