Applied Probability and Stochastic Processes OpenCourseWare: A Free Graduate Level Course on Applied Probability by MIT
Learn how to use mathematical probability in practical applications with this free online OpenCourseWare from the Massachusetts Institute of Technology. 'Special Seminar in Applied Probability and Stochastic Processes' explores the use of complex probabilities in the fields of physics, computer science and engineering. This advanced graduate-level course is recommended for students studying Math, Physics, Computer Science or Engineering.
Special Seminar in Applied Probability and Stochastic Processes: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Graduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | Yes | No |
Special Seminar in Applied Probability and Stochastic Processes: Course Description
Many fields of applied math and science use probability and stochastic processes to build machines and understand physical phenomena. MIT's 'Applied Probability and Stochastic Processes' explores the use of applied probability in physics, computer science and engineering. In physics, the use of probabilistic math allows students to explore that are difficult to replicate experimentally, such as the random magnetic interactions in a spin glass. Computer science topics covered in the course include the use of belief propagation algorithms in artificial intelligence. The course explores the use of probability in electrical engineering in building models to transmit information over noisy channels, specifically in low density parity check (LDPC) codes. This is an advanced graduate-level course taught by MIT Professors David Gamarnik and Devavrat Shah and is recommended for doctoral students with a background in optimization, probability and algorithms.
Readings and lecture summaries are available for download on the course website. To learn more, visit probability and stochastic processes course page.
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