Mathematical Tools for Neuroscience

Catalog description

Student-instructed. This course aims to equip biosciences graduate students with the fundamental skills in quantitative modeling and data analysis necessary for neuroscience research. It covers techniques including linear algebra, Fourier transforms, probability and statistics, signal detection, statistical inference, and information theory. The course is required for first-year students in the Neuroscience PhD program, and is open to other graduate students in the biosciences. Other students, including undergraduates, may enroll by special request.