C06 Linear Algebra and Optimization

Offered under: 6.C01, 18.C06
Term(s): Fall
Level: Undergraduate
Units: 12
Prerequisite: Calculus II
Instructors: Ankur Moitra (Mathematics), Pablo Parrilo (EECS)

Covers same fundamental concepts as 18.06 Linear Algebra with a view toward modeling, computation, and applications. Integrates geometric, algebraic, and computational viewpoints. Satisfies a General Institute Requirement (REST).

Unified introduction to linear algebra and optimization, their interconnections, and applications throughout science and engineering. Topics include: vectors, matrices, eigenvalues, singular values, least-squares, convex optimization, linear/quadratic programming, gradient descent, Newton’s method. Viewpoint will emphasize conceptual, geometric, and computational aspects. Applications from many domains, including networks, signal processing, and machine learning.
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