Stanford Algorithms Specialization

Part I

1. Introduction; "big-oh" notation and asymptotic analysis.
   Project: Karatsuba multiplication

2. Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
   Project: count inverse

3. The QuickSort algorithm and its analysis; probability review.
   Project: quick sort

4. Linear-time selection; graphs, cuts, and the contraction algorithm.
   Project: Karger's algorithm

Part II

5. Breadth-first and depth-first search; computing strong components; applications.
   Project: Kosaraju's algorithm

6. Dijkstra's shortest-path algorithm.
   Project: Dijkstra's algorithm

7. Heaps; balanced binary search trees.
   Project: median maintenance problem

8. Hashing; bloom filters.
   Project: two sum

Part III

9. Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
   Project: job scheduling
   Project: Prims's MST algorithm

10. Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
    Project: max-spacing k-clustering

11. Huffman codes; introduction to dynamic programming.
    Project: Huffman coding
    Project: max-weight independent set

12. Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
    Project: knapsack problem

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