MATH 320
Algorithm Design and Optimization 1
Mathematics
College of Physical and Mathematical Sciences
Course Description
A treatment of algorithms used to solve problems. Topics include complexity and data, approximation theory, recursive algorithms, linear optimization, unconstrained optimization, constrained optimization, global optimization.
When Taught
Fall
Grade Rule
Grade Rule 8: A, B, C, D, E, I (Standard grade rule)
Min
3
Fixed
3
Fixed
3
Fixed
0
Other Prerequisites
concurrent enrollment in Math 321, 344.
Note
Students who register for MATH 320 must also register for the same section of MATH 344 and register for MATH 321 and MATH 345.
Title
Introduction to Algorithms and Approximation
Learning Outcome
Coverage of the fundamentals of algorithm analysis including, convergence, stability, mathematics for algorithm analysis, data structures, probability, and introductory statistics. Discrete optimization and algorithms employing stochastic guessing are investigated. Additionally, students will learn about approximation methods including Fourier series and wavelets. For detailed information about desired learning outcomes visit the Math 320 Wiki page.
