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Oct 02, 2024
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MATH 403 - Linear Algebra and Modeling for Data Science 3 Credits
Description Foundations of using matrices, differential equations and other models in modeling. The course takes the theoretical models and focuses on computational solutions and modeling in a modern programming language and modeling environment. Topics include matrices and determinants, systems of linear equations, vector spaces, linear transformations, eigenvalues and eigenvectors, singular value decompositions, orthogonal matrices, mathematical modeling using differential equations, optimization and applications. Focus is on how the models and tools are applied in data science and analytics.
Prerequisites MATH 252, MATH 313, MATH 320, MATH 341, and CS 201
Repeatable No
Foundational Studies Credit No
Click here for the Fall 2024 Class Schedule
Click here for the Spring 2025 Class Schedule
Click here for the Summer 2025 Class Schedule
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