Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. 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.
About the instructor: Tim Roughgarden has been a professor in the Computer Science Department at Stanford University since 2004. He has taught and published extensively on the subject of algorithms and their applications.
- INTRODUCTION
- ASYMPTOTIC ANALYSIS
- DIVIDE & CONQUER ALGORITHMS
- THE MASTER METHOD
- QUICKSORT - ALGORITHM
- QUICKSORT - ANALYSIS
- PROBABILITY REVIEW
- LINEAR-TIME SELECTION
- GRAPHS AND THE CONTRACTION ALGORITHM
- GRAPH SEARCH AND CONNECTIVITY
- DIJKSTRA'S SHORTEST-PATH ALGORITHM
- HEAPS
- BALANCED BINARY SEARCH TREES
- HASHING: THE BASICS
- UNIVERSAL HASHING
- BLOOM FILTERS
- 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
- 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