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 ...

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, ...

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 ...

The project required bringing together years of research in approximate dynamic programming, merging math programming with machine learning, to solve dynamic programs with extremely high-dimensional ...

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

Thinking about getting good at competitive programming, especially on a platform like CodeChef? It can seem like ...

The Dynamic Programming and Optimal Control class focuses on optimal path planning and solving optimal control problems for dynamic systems. It stands out for several reasons: It is multidisciplinary, ...

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...