IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

Dynamic Programming, Greedy Algorithms can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.

View on Coursera Course Description This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

Brief Description of Course Content Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and ...

Hugo P. Simão, Jeff Day, Abraham P. George, Ted Gifford, John Nienow, Warren B. Powell, An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application, ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

Manuel S. Santos, , Analysis of a Numerical Dynamic Programming Algorithm Applied to Economic Models, Econometrica, Vol. 66, No. 2 (Mar., 1998), pp. 409-426 ...