Course Information
Description
Introductory course in linear algebra and optimization, assuming no prior exposure to linear algebra and starting from the basics, including vectors, matrices, eigenvalues, singular values, and least squares. Covers the basics in optimization including convex optimization, linear/quadratic programming, gradient descent, and regularization, building on insights from linear algebra. Explores a variety of applications in science and engineering, where the tools developed give powerful ways to understand complex systems and also extract structure from data.
Class Notes
See MIT Schedule for times and locations;
Faculty: Ankur Moitra;
Prereq: Calculus II (GIR);
Subject Level: Undergraduate
School
Non-Harvard
Units
12
Cross Reg
Available for Harvard Cross Registration
Department
Mass Institute of Technology
Course Component
Regular Course
Subject
MIT Mathematics
Grading Basis
MIT Optional (LG/AUD)
