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.

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

Dynamic programming algorithms are developed for optimal capital allocation subject to budget constraints. We extend the work of Weingartner [17] and Weingartner and Ness [19] by including multilevel ...

CS 336 or Permission of Instructor Description This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, ...

In this paper we develop a discretized version of the dynamic programming algorithm and study its convergence and stability properties. We show that the computed value function converges quadratically ...

Dynamic Programming and Optimal Control 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 ...

Understand the various algorithms for solving a dynamic program Topics Introduction to dynamic programming Value and policy iterations Stochastic gradient algorithm Q-learning and temporal differences ...

Greedy Algorithms Dynamic Programming Algorithms Algorithms for the following primitives: Sorting: bubblesort, mergesort, heapsort, quicksort. Searching Graph Algorithms: Depth/Breadth First Search, ...