Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Offered By: Stanford University via Coursera
Course Description
Overview
The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Syllabus
- Week 1
- Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
- Week 2
- Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
- Week 3
- Huffman codes; introduction to dynamic programming.
- Week 4
- Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
Taught by
Tim Roughgarden
Tags
Related Courses
Graph Partitioning and ExpandersStanford University via NovoEd The Analytics Edge
Massachusetts Institute of Technology via edX More Data Mining with Weka
University of Waikato via Independent Mining Massive Datasets
Stanford University via edX The Caltech-JPL Summer School on Big Data Analytics
California Institute of Technology via Coursera