Course Description
Summary
Together with calculus, linear algebra is one of the foundations of higher-level mathematics and its applications. This is NOT just the algebra you know from high school. There are several perspectives one can take on linear algebra: it is a method for handling large systems of linear equations, it is a theory of linear geometry (including in dimensions larger than three), it is matrix algebra, and it is a theoretical structure that appears throughout mathematics, physics, computer science, and statistics. This course is necessary for students concentrating in mathematics, physics, or computer science, and may be useful to students in other sciences, economics, or any studies involving statistics. This course is a prerequisite for Multivariable Calculus. Applications of linear algebra include correlation coefficients and linear regression in statistics, finite element methods in physics and engineering, analysis of networks, computer graphics, google page rank, error-correcting codes, and data compression. (Linear algebra is also central to quantum mechanics, though we will not cover that application.) The focus of the course is on core concepts, introduced with examples and computations, and applications. The course is not proof-based; students wanting to do more advanced theory or applications should continue to Advanced Linear Algebra.
