Computer Science 341SC - Scientific Computing

The goal of this course is to study the most fundamental numerical algorithms for solving some of the more mathematical research and practice problems that arise in computer science. In this course, you will practice and develop algorithms to solve linear and nonlinear systems for given problems in computer science contexts like vision, machine learning, and robotics. Topics include understanding the errors caused by computer approximation, linear least squares, nonlinear equations, optimization, and polynomial interpolation. At the end of the semester, we will also practice the course material by working through the mathematical details in some classical research papers on image processing and computer vision. This course is programming-intensive and will introduce Python.

Prereq: MATH-211.