Advanced Stochastic Processes OpenCourseWare: MIT's Free Graduate Level Course on Stochastic Process Analysis
The OpenCourseWare 'Advanced Stochastic Processes' is about the modeling and analysis of stochastic processes. MIT's business master's students take this graduate-level course.
Advanced Stochastic Processes: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Graduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | No | Yes |
Advanced Stochastic Processes: Course Description
Professor David Gamarnik and Premal Shah taught this graduate-level course. The course focuses on the mathematical properties and analysis of random processes. Starting with probability basics, random variables, i.i.d. (independent and identically distributed) random variables and Strong Law, the class then looks at Brownian motion, convergence modes, conditional expectations, filtration, martingales and stopping times. Students are introduced to Itô calculus (Kiyoshi Itô advanced calculus methods to stochastic processes). Other topics include Girsanov Theorem, queuing networks and reflected Brownian motion.
The OpenCourseWare version includes lecture notes for all 25 classes. Six problem sets and two exams are also included, but without solutions. To take this free course, go to the course page for ''Advanced Stochastic Processes.''
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