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Summer 2022
Jun 14, 2024
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CSC 340 - Scientific Computing
Introduction to the design, application, and performance of numerical algorithms fundamental to scientific computation. Topics may include error and error propagation; matrix applications such as finding solutions to linear systems, finding eigenvalues and eigenvectors, or finding linear principal components; optimization; basic Markov modeling; Fourier processing; and curve fitting. Emphasizes relative merits and implementations of algorithms.
3.000 Credit hours
3.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Computer Science Department

Restrictions:
May not be assigned one of the following Student Attributes:     
      Online Accelerated Programs

Prerequisites:
Undergraduate level MAT 162 Minimum Grade of D- and Undergraduate level CSC 231 Minimum Grade of C

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