PLEASE see Announcements for information regarding remote learning for this course.

This course presents a survey of computational algorithms for students
who are interested in solving problems from a variety of scientific
disciplines. Mathematical modeling is often used to describe a
phenomenon of interest, but the model is typically too complex to
construct an analytical solution. Numerical algorithms are therefore
needed to find a solution that best describes the phenomenon of
interest. The survey of numerical methods will be motivated by models
that describe events in physics, biology, medicine and will focus on
data driven applications. The students will learn appropriate
numerical algorithms, as well as how to critically analyze the quality of their results. Specifically, students will mathematically analyze the accuracy, efficiency and convergence properties of their techniques.
results. Although programming will not be formally taught as part of the course, students will write numerical code in languages such as MATLAB to compute their solutions. Resources will be provided to help students learn to write MATLAB code.

**Course Objectives:**Students will master a suite of computational tools for approximating solutions to complex mathematical models. Students will understand how implement algorithms to generate these solutions and evaluate their quality and accuracy. This is

*not*a survey course, although students will program methods to gain understanding of how methods work, in particular to compare advantages and disadvantages of various algorithms.