*
    *     Introduction
        *     
 Algorithms: Introduction (09:23 mins)
    *     Lecture 1: Union-Find
        *     
 Dynamic Connectivity (10:23 mins)
        *     
 Quick Find (10:19 mins)
        *     
 Quick Union (07:51 mins)
        *     
 Quick-Union Improvements (13:03 mins)
        *     
 Union-Find Applications (09:22 mins)
    *     Lecture 2: Analysis of Algorithms
        *     
 Introduction to Analysis of Algorithms (08:15 mins)
        *     
 Observations (10:06 mins)
        *     
 Mathematical Models (12:49 mins)
        *     
 Order-of-Growth Classifications (14:40 mins)
        *     
 Theory of Algorithms (11:36 mins)
        *     
 Memory (08:12 mins)
    *     Lecture 3: Stacks and Queues
        *     
 Stacks (16:24 mins)
        *     
 Resizing Arrays (09:57 mins)
        *     
 Queues (04:34 mins)
        *     
 Generics (09:27 mins)
        *     
 Iterators (07:17 mins)
        *     
 Stack and Queue Applications (13:25 mins)
    *     Lecture 4: Elementary Sorts
        *     
 Introduction to Sorting (14:43 mins)
        *     
 Selection Sort (06:59 mins)
        *     
 Insertion Sort (09:29 mins)
        *     
 Shellsort (10:49 mins)
        *     
 Shuffling (07:40 mins)
        *     
 Convex Hull (13:51 mins)
    *     Lecture 5: Mergesort
        *     
 Mergesort (23:55 mins)
        *     
 Bottom-up Mergesort (03:21 mins)
        *     
 Sorting Complexity (09:06 mins)
        *     
 Comparators (06:44 mins)
        *     
 Stability (05:40 mins)
    *     Lecture 6: Quicksort
        *     
 Quicksort (19:34 mins)
        *     
 Selection (07:09 mins)
        *     
 Duplicate Keys (11:26 mins)
        *     
 System Sorts (11:50 mins)
    *     Lecture 7: Priority Queues
        *     
 APIs and Elementary Implementations (12:53 mins)
        *     
 Binary Heaps (23:37 mins)
        *     
 Heapsort (14:30 mins)
        *     
 Event-Driven Simulation (22:39 mins)
    *     Lecture 8: Elementary Symbol Tables
        *     
 Symbol Table APIs (21:31 mins)
        *     
 Elementary Implementations (09:04 mins)
        *     
 Ordered Operations (06:26 mins)
        *     
 Binary Search Trees (19:57 mins)
        *     
 Ordered Operations in BSTs (10:32 mins)
        *     
 Deletion in BSTs (09:53 mins)
    *     Lecture 9: Balanced Search Trees
        *     
 Search Trees (16:56 mins)
        *     
 Red-Black BSTs (35:30 mins)
        *     
 B-Trees (10:37 mins)
    *     Lecture 10: Geometric Applications of BSTs
        *     
 Range Search (08:52 mins)
        *     
 Line Segment Intersection (05:47 mins)
        *     
 Kd-Trees (29:08 mins)
        *     
 Interval Search Trees (13:47 mins)
        *     
 Rectangle Intersection (08:11 mins)
    *     Lecture 11: Hash Tables
        *     
 Hash Functions (18:14 mins)
        *     
 Separate Chaining (07:28 mins)
        *     
 Linear Probing (14:38 mins)
        *     
 Context (10:10 mins)
        *     
 Sets (05:05 mins)
        *     
 Dictionary Clients (05:39 mins)
        *     
 Indexing Clients (07:53 mins)
        *     
 Sparse Vectors (07:42 mins)
    *     Lecture 12: Undirected Graphs
        *     
 Introduction to Graphs (09:33 mins)
        *     
 Graph API (14:47 mins)
        *     
 Depth-First Search (26:23 mins)
        *     
 Breadth-First Search (13:34 mins)
        *     
 Connected Components (18:56 mins)
        *     
 Graph Challenges (14:29 mins)
    *     Lecture 13: Directed Graphs
        *     
 Introduction to Digraphs (08:31 mins)
        *     
 Digraph API (04:56 mins)
        *     
 Digraph Search (20:57 mins)
        *     
 Topological Sort (12:54 mins)
        *     
 Strong Components (20:22 mins)
    *     Lecture 14: Minimum Spanning Trees
        *     
 Introduction to MSTs (04:04 mins)
        *     
 Greedy Algorithm (12:57 mins)
        *     
 Edge-Weighted Graph API (11:16 mins)
        *     
 Kruskal's Algorithm (12:29 mins)
        *     
 Prim's Algorithm (33:16 mins)
        *     
 MST Context (10:35 mins)
    *     Lecture 15: Shortest Paths
        *     
 Shortest Paths APIs (10:51 mins)
        *     
 Shortest Path Properties (14:46 mins)
        *     
 Dijkstra's Algorithm (18:58 mins)
        *     
 Edge-Weighted DAGs (19:24 mins)
        *     
 Negative Weights (21:02 mins)
    *     Lecture 16: Maximum Flow and Minimum Cut
        *     
 Introduction to Maxflow (10:34 mins)
        *     
 Ford-Fulkerson Algorithm (06:33 mins)
        *     
 Maxflow-Mincut Theorem (09:39 mins)
        *     
 Running Time Analysis (08:50 mins)
        *     
 Java Implementation (14:29 mins)
        *     
 Maxflow Applications (22:20 mins)
    *     Lecture 17: Radix Sorts
        *     
 Strings in Java (17:43 mins)
        *     
 Key-Indexed Counting (12:07 mins)
        *     
 LSD Radix Sort (15:01 mins)
        *     
 MSD Radix Sort (13:42 mins)
        *     
 3-way Radix Quicksort (07:23 mins)
        *     
 Suffix Arrays (19:25 mins)
    *     Lecture 18: Tries
        *     
 R-way Tries (32:19 mins)
        *     
 Ternary Search Tries (22:43 mins)
        *     
 Character-Based Operations (20:04 mins)
    *     Lecture 19: Substring Search
        *     
 Introduction to Substring Search (06:42 mins)
        *     
 Brute-Force Substring Search (10:11 mins)
        *     
 Knuth-Morris-Pratt (33:15 mins)
        *     
 Boyer-Moore (08:37 mins)
        *     
 Rabin-Karp (16:14 mins)
    *     Lecture 20: Regular Expressions
        *     
 Regular Expressions (20:03 mins)
        *     
 REs and NFAs (13:14 mins)
        *     
 NFA Simulation (18:24 mins)
        *     
 NFA Construction (11:43 mins)
        *     
 Regular Expression Applications (20:06 mins)
    *     Lecture 21: Data Compression
        *     
 Introduction to Data Compression (22:27 mins)
        *     
 Run-Length Coding (05:59 mins)
        *     
 Huffman Compression (24:15 mins)
        *     
 LZW Compression (27:33 mins)
    *     Lecture 22: Reductions
        *     
 Introduction to Reductions (09:32 mins)
        *     
 Designing Algorithms (08:13 mins)
        *     
 Establishing Lower Bounds (09:23 mins)
        *     
 Classifying Problems (12:45 mins)
    *     Lecture 23: Linear Programming
        *     
 Brewer's Problem (21:16 mins)
        *     
 Simplex Algorithm (11:49 mins)
        *     
 Simplex Implementations (16:22 mins)
        *     
 Linear Programming Reductions (11:46 mins)
    *     Lecture 24: Intractability
        *     
 Introduction to Intractability (17:01 mins)
        *     
 Search Problems (10:57 mins)
        *     
 P vs. NP (16:30 mins)
        *     
 Classifying Problems (13:43 mins)
        *     
 NP-Completeness (12:38 mins)
        *     
 Coping with Intractability (14:02 mins)