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Dec 21, 2024
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CSCI 2033 - Elementary Computational Linear Algebra Credits: 4 Hours/Week: Lecture 4 Lab None Course Description: This course is an introduction to the numerical methods of Linear Algebra and their application to solving computational problems. Topics covered will include matrices, linear transformations, linear vector spaces, inner product spaces, systems of linear equations, Eigenvalues, and singular values. Algorithms and computational matrix methods will be presented using MATLAB. Matrix methods will be used to solve a variety of computer science problems. MnTC Goals None
Prerequisite(s): MATH 1081 , CSCI 1081 or college-level course in programming Corequisite(s): None Recommendation: None
Major Content
- Vectors; linear combinations; matrices; matrix operations
- Elementary linear mappings; applications in graphics and statistics
- Systems of linear equations; applications
- Theory of linear equations: complexity, operation counts; applications
- Vector spaces; abstract linear spaces; subspaces; linear dependence; basis and dimensions; row reduced form; null space; range; Applications
- Determinants Theory; Proofs; Applications
- Inner Products.; Orthogonality; Least Squares; Norms, Condition Numbers, and Numerical Stability; Applications
- Abstract linear transformations; Applications
- Eigenvalues. Spectra of Symmetric matrices; Diagonalization of symmetric matrices; Applications
- Singular Value Decomposition; Applications
Learning Outcomes At the end of this course students will be able to:
- demonstrate an understanding of the basic theorems and techniques of linear algebra
- develop the numerical methods which approximate linear algebraic equations
- create and apply appropriate algorithms and numerical methods to solve a variety of problems
- use Matlab (or similar tool) to implement algorithms and computational methods
- use symbolic methods to identify and solve linear algebraic problem
Competency 1 (1-6) None Competency 2 (7-10) None Courses and Registration
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