Numerical Methods for Partial Differential Equations OpenCourseWare: A Free Graduate Level Differential Equations Course by MIT
MIT has put 'Numerical Methods for Partial Differential Equations' into its OpenCourseWare. This course was part of the curricula of the Departments of Aeronautics and Astronautics, Electrical Engineering and Computer Science and Mechanical Engineering and offered through SMA (Singapore-MIT Alliance). The course covers solving partial differential equations using numerical techniques and examines problems relevant to the fields of engineering and science.
Numerical Methods for Partial Differential Equations: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Graduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | Yes | No |
Numerical Methods for Partial Differential Equations: Course Description
Partial Differential Equations (PDEs) are mathematical equations that deal with a function and its partial derivative. PDEs are generally much more complex and much more difficult to solve than 'normal' differential equations. Numerical methods, also known as numerical analysis, deal with approximating an answer as closely as possible within certain pre-defined limits using a variety of mathematical techniques. This course applies these numerical method techniques to the solving of complex PDEs, which have practical application in science and engineering fields. The original course covered Nystrom methods, conservation laws, elliptic problems, iterative methods, derivation and convergence theory. Previous experience with differential equations, linear algebra and MATLAB is necessary. Professors Jaime Peraire, Anthony T. Patera, Jacob White and Boo Cheong Khoo originally taught the course in a lecture-style format to graduates in astronautics, aeronautics, mechanical and electrical engineering and computer science.
Users of this OpenCourseWare can access course handouts, in-class lecture slides, a reading list and assignments. If you're wild about partial differential equations and want to learn more, then visit the numerical techniques and partial differential equations.