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Oct 23, 2026
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MATH 2200 - Linear Algebra
Credits: 4
Catalog Description
Intended for students in the areas of engineering, sciences, or mathematics. This course serves these students with both practical applications of mathematics and as a bridge between lower-level mathematics courses and higher-level (often more theoretical) mathematics. Topics include matrix operations; systems of linear equations; Gaussian elimination; determinants; matrix inverses; vectors; vector spaces; subspaces; linear independence; linear transformations; matrix transformations; dimension; eigenvalues and eigenvectors; diagonalization; and orthogonality. Supplementary topics and technology-based assignments may vary.
Prerequisite(s) (must have a grade of C or better): MATH 1401 with a grade of C or better, or equivalent
Additional fee to student: No
Learner Outcomes
- Apply linear algebra techniques in order to solve a wide a variety of problems encountered in the mathematical and engineering areas.
- Perform various matrix operations including addition, subtraction, and multiplications (of matrices and by a scalar).
- Find the inverse of a non-singular matrix.
- Perform Gaussian elimination in order to find the solution set for a given system of linear equations.
- Find the determinant of a given n by n matrix.
- Understand and use properties of determinants.
- Determine whether a set of vectors is a subspace or just a subset of a given vector space.
- Determine whether a set of vectors is linearly independent.
- Find the eigenvalues and the corresponding eigenvectors for a given n by n matrix.
- Diagonalize an n by n matrix with n linearly independent eigenvectors.
- Determine whether a transformation is a linear transformation.
- Use dot products for orthogonal projections.
- Use eigenvalues and eigenvectors to understand discrete dynamical systems.
- Use the Gram-Schmidt process to create an orthogonal and an orthonormal basis for a vector space.
- Solve least-square problems.
- Diagonalize symmetric matrices and use the diagonalization to understand quadratic forms.
Major Areas of Course Content
- Matrix Operations
- Systems of Linear Equations
- Determinants
- Vectors and Vector Spaces
- Linear Transformation
- Eigenvalues and Eigenvectors
- Orthogonality
- Supplementary Topics (chosen from topics such as various matrix factorizations, complex eigenvalues and eigenvectors, inner product spaces, and encryption)
- Supplementary Applications (chosen from Markov chains, input-output models, difference equations, differential equations, linear programming)
- Technology-based Assignments
Credit for Prior Learning Options
Course-Specific Exam
Credit for Prior Learning Option Procedure(s)
- The student should contact an instructor currently teaching or scheduled to teach the desired course.
- The instructor will provide and schedule an exam date.
- The student is to bring the Credit by Exam form to the scheduled exam.
- The faculty member will notify the student and Records Office of the results.
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