Introduction to Algorithms and Approximation
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.