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.
Learning Outcomes:
- Work with Gauss-Jordan elimination and with matrix algebra; visualize linear systems and write graphical transformations in matrix form
- Understand the elementary theory of determinants
- Be familiar with applications of linear algebra, and recognize when a problem is amenable to linear algebra techniques
- Be able to translate between systems of linear equations, graphical intuition, matrix algebra, and higher-level concepts
- Learn to test validity of proposed solutions
- Get practice in making conjectures and asking good questions
- Continue to develop higher-order conceptual thinking in mathematics ("mathematical maturity")
Delivery Method: Remotely accessible
Course Level: 2000-level
Credits: 4
T/F 2:10PM - 4:00PM (Full-term)
Maximum Enrollment: 20
Course Frequency: Once a year
Categories: All courses , Mathematics , Remotely Accessible
Tags: Quantitative reasoning