1. Introduction to Data Structures and Algorithms
2. Stacks
3. Queues and Linked Lists
4. Dictionaries
5. Hashing
6. Trees
7. Tree Walks / Traversals
8. Ordered Dictionaries
9. Deletion
10. Quick Sort
11. AVL Trees
12. AVL Trees
13. Trees
14. Red Black Trees
15. Insertion in Red Black Trees
16. Disk Based Data Structures
17. Case Study: Searching for Patterns
18. Tries
19. Data Compression
20. Priority Queues
21. Binary Heaps
22. Why Sorting
23. More Sorting
24. Graphs
25. Data Structures for Graphs
26. Two Applications of Breadth First Search
27. Depth First Search
28. Applications of DFS
29. DFS in Directed Graphs
30. Applications of DFS in Directed Graphs
31. Minimum Spanning Trees
32. The Union
33. Prims Algorithm for Minimum Spanning Trees
34. Single Source Shortest Paths
35. Correctness of Dijkstras Algorithm
36. Single Source Shortest Paths

The objective of the course is to familiarize students with basic data structures and their use in fundamental algorithms. Course contents: Introduction to object oriented programming through stacks, queues and linked lists. Dictionaries: skip-lists, hashing, analysis of collision resolution techniques. Trees, traversals, binary search trees, optimal and average BST's. 2-4 trees and red-black trees. Tries and pattern matching. Priority queues and binary heaps. Sorting: merge, quick, radix, selection, heap. Graphs, Breadth first search and connected components. Depth first search in directed and undirected graphs and strongly connected components. Spanning trees: Prim's and Kruskal's algorithm, union-find data structure. Dijkstra's algorithm for shortest paths, shortest path tree. Directed acyclic graphs: topological sort and longest path.