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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