Dynamic Programming and Stochastic Control OpenCourseWare: A Free Online Graduate Level Programming Course by MIT
Graduate students can learn new sequential problem-solving techniques for stochastic control in the 'Dynamic Programming and Stochastic Control' OpenCourseWare. The free online course is offered by the Massachusetts Institute of Technology (MIT) and is part of the Electrical Engineering and Computer Science Department.
Dynamic Programming and Stochastic Control: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Graduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | Yes | Yes |
Dynamic Programming and Stochastic Control: Course Specifics
In the 'Dynamic Programming and Stochastic Control' OpenCourseWare, graduate students can learn about problem-solving techniques for sequential decision making with stochastic control. Students can also learn about various methods of addressing large state spaces in this free online course. The on-campus MIT course was taught by Professor Dimitri Bertsekas in the fall of 2002. The course was taught as a lecture class for two hours, one session per week. Some of the lecture topics discussed include dynamic programming algorithms, stopping and scheduling programs, infinite horizon problems, average cost problems, linear quadratic problems and shortest path algorithms. Students taking this free online course should have advanced math skills and previous knowledge of probability and Markov chains. The materials used for this course are generated from Professor Bertsekas' textbook 'Dynamic Programming and Optimal Control.'
This OpenCourseWare includes lecture notes, assignment solutions and sample exams. If you are interested in taking this free course, visit the stochastic control and dynamic programming course page.
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