CS 357

CS 357 - Numerical Methods I

Spring 2025

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Numerical Methods ICS357M61476PKG3 -    Mariana Silva
Numerical Methods ICS357M61476PKG31230 - 1345 T R    Mariana Silva
Numerical Methods ICS357N50106LCD31230 - 1345 T R  0035 Campus Instructional Facility Mariana Silva
Numerical Methods IMATH357M61477PKG31230 - 1345 T R    Mariana Silva
Numerical Methods IMATH357M61477PKG3 -    Mariana Silva
Numerical Methods IMATH357N50107LCD31230 - 1345 T R  0035 Campus Instructional Facility Mariana Silva

Official Description

Fundamentals of numerical methods for students in science and engineering; floating-point computation, systems of linear equations, approximation of functions and integrals, the single nonlinear equation, and the numerical solution of ordinary differential equations; various applications in science and engineering; programming exercises and use of high quality mathematical library routines. Course Information: Same as MATH 357. Credit is not given towards graduation for CS 357 if credit for CS 450 has been earned. (Counts for advanced hours in LAS). Prerequisite: One of CS 101, CS 105, CS 124, CS 125 or ECE 220; MATH 241; one of MATH 225, MATH 257, MATH 415, MATH 416, ASRM 406 or BIOE 210.

Text(s)


Varies by semester

Learning Goals


Analyze the sources of errors in mathematical operations on the computer (2)
Implement and analyze major numerical methods and their merits and pitfalls (1), (6)
Calculate the computational cost of a range of numerical methods (2)
Select and use software tools, based on their numerical methods, for a range of problems (1), (6)
Estimate the accuracy in approximated numerical solutions (2), (6)

Topic List

Numerical experiments, randomness, Monte Carlo simulations

· Errors (rounding and truncation)

· Taylor series

· Floating point representation and operations

· Linear system of equations

· Sparse matrix storage and computation

· Eigenvalue problems

· Low rank approximations

· Least squares problems

· Interpolation

· Root finding

· Nonlinear Optimization

Assessment and Revisions

Revisions in last 6 years Approximately when revision was done Reason for revision Data or documentation available?
no significant revisions

Required, Elective, or Selected Elective

Required.

Last updated

2/10/2019by Mariana Silva