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https://github.com/extwiii/algorithms-stanford.university

Algorithms - Learn To Think Like A Computer Scientist - Coursera
https://github.com/extwiii/algorithms-stanford.university

algorithm analysis computer-scientists graph-search greedy-algorithms minimum-spanning-trees quicksort shortest-paths stanford-university

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Algorithms - Learn To Think Like A Computer Scientist - Coursera

Host: GitHub
URL: https://github.com/extwiii/algorithms-stanford.university
Owner: extwiii
License: apache-2.0
Created: 2017-01-01T21:22:10.000Z (about 8 years ago)
Default Branch: master
Last Pushed: 2017-02-02T18:11:39.000Z (almost 8 years ago)
Last Synced: 2024-11-29T23:12:16.436Z (2 months ago)
Topics: algorithm, analysis, computer-scientists, graph-search, greedy-algorithms, minimum-spanning-trees, quicksort, shortest-paths, stanford-university
Size: 78.1 MB
Stars: 2
Watchers: 3
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

# Algorithms-Stanford.University
* Learn To Think Like A Computer Scientist, Algorithms - Stanford University - Coursera

This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.

## Course 1 - Divide and Conquer, Sorting and Searching, and Randomized Algorithms
* INTRODUCTION
* ASYMPTOTIC ANALYSIS
* DIVIDE & CONQUER ALGORITHMS
* THE MASTER METHOD
* QUICKSORT - ALGORITHM
* QUICKSORT - ANALYSIS
* PROBABILITY REVIEW
* LINEAR-TIME SELECTION
* GRAPHS AND THE CONTRACTION ALGORITHM

## Course 2 - Graph Search, Shortest Paths, and Data Structures
* GRAPH SEARCH AND CONNECTIVITY
* DIJKSTRA'S SHORTEST-PATH ALGORITHM
* HEAPS
* BALANCED BINARY SEARCH TREES
* HASHING: THE BASICS
* UNIVERSAL HASHING
* BLOOM FILTERS

## Course 3 - Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
* TWO MOTIVATING APPLICATIONS
* INTRODUCTION TO GREEDY ALGORITHMS
* A SCHEDULING APPLICATION
* PRIM'S MINIMUM SPANNING TREE ALGORITHM
* KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM
* CLUSTERING
* ADVANCED UNION-FIND
* HUFFMAN CODES
* INTRODUCTION TO DYNAMIC PROGRAMMING
* THE KNAPSACK PROBLEM
* SEQUENCE ALIGNMENT
* OPTIMAL BINARY SEARCH TREES

## Course 4 - Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
* THE BELLMAN-FORD ALGORITHM
* ALL-PAIRS SHORTEST PATHS
* NP-COMPLETE PROBLEMS
* FASTER EXACT ALGORITHMS FOR NP-COMPLETE PROBLEMS
* APPROXIMATION ALGORITHMS FOR NP-COMPLETE PROBLEMS
* LOCAL SEARCH ALGORITHMS
* THE WIDER WORLD OF ALGORITHMS

#### Taught by:
* Tim Roughgarden - Associate Professor, Computer Science

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