**Oreilly - Algorithms: 24-part Lecture Series**

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- Introduction
- Algorithms: Introduction 00:09:23

- Lecture 1: Union-Find
- Dynamic Connectivity 00:10:23
- Quick Find 00:10:19
- Quick Union 00:07:51
- Quick-Union Improvements 00:13:03
- Union-Find Applications 00:09:22

- Lecture 2: Analysis of Algorithms
- Introduction to Analysis of Algorithms 00:08:15
- Observations 00:10:06
- Mathematical Models 00:12:49
- Order-of-Growth Classifications 00:14:40
- Theory of Algorithms 00:11:36
- Memory 00:08:12

- Lecture 3: Stacks and Queues
- Stacks 00:16:24
- Resizing Arrays 00:09:57
- Queues 00:04:34
- Generics 00:09:27
- Iterators 00:07:17
- Stack and Queue Applications 00:13:25

- Lecture 4: Elementary Sorts
- Introduction to Sorting 00:14:43
- Selection Sort 00:06:59
- Insertion Sort 00:09:29
- Shellsort 00:10:49
- Shuffling 00:07:40
- Convex Hull 00:13:51

- Lecture 5: Mergesort
- Mergesort 00:23:55
- Bottom-up Mergesort 00:03:21
- Sorting Complexity 00:09:06
- Comparators 00:06:44
- Stability 00:05:40

- Lecture 6: Quicksort
- Quicksort 00:19:34
- Selection 00:07:09
- Duplicate Keys 00:11:26
- System Sorts 00:11:50

- Lecture 7: Priority Queues
- APIs and Elementary Implementations 00:12:53
- Binary Heaps 00:23:37
- Heapsort 00:14:30
- Event-Driven Simulation 00:22:39

- Lecture 8: Elementary Symbol Tables
- Symbol Table APIs 00:21:31
- Elementary Implementations 00:09:04
- Ordered Operations 00:06:26
- Binary Search Trees 00:19:57
- Ordered Operations in BSTs 00:10:32
- Deletion in BSTs 00:09:53

- Lecture 9: Balanced Search Trees
- Search Trees 00:16:56
- Red-Black BSTs 00:35:30
- B-Trees 00:10:37

- Lecture 10: Geometric Applications of BSTs
- Range Search 00:08:52
- Line Segment Intersection 00:05:47
- Kd-Trees 00:29:08
- Interval Search Trees 00:13:47
- Rectangle Intersection 00:08:11

- Lecture 11: Hash Tables
- Hash Functions 00:18:14
- Separate Chaining 00:07:28
- Linear Probing 00:14:38
- Context 00:10:10
- Sets 00:05:05
- Dictionary Clients 00:05:39
- Indexing Clients 00:07:53
- Sparse Vectors 00:07:42

- Lecture 12: Undirected Graphs
- Introduction to Graphs 00:09:33
- Graph API 00:14:47
- Depth-First Search 00:26:23
- Breadth-First Search 00:13:34
- Connected Components 00:18:56
- Graph Challenges 00:14:29

- Lecture 13: Directed Graphs
- Introduction to Digraphs 00:08:31
- Digraph API 00:04:56
- Digraph Search 00:20:57
- Topological Sort 00:12:54
- Strong Components 00:20:22

- Lecture 14: Minimum Spanning Trees
- Introduction to MSTs 00:04:04
- Greedy Algorithm 00:12:57
- Edge-Weighted Graph API 00:11:16
- Kruskal's Algorithm 00:12:29
- Prim's Algorithm 00:33:16
- MST Context 00:10:35

- Lecture 15: Shortest Paths
- Shortest Paths APIs 00:10:51
- Shortest Path Properties 00:14:46
- Dijkstra's Algorithm 00:18:58
- Edge-Weighted DAGs 00:19:24
- Negative Weights 00:21:02

- Lecture 16: Maximum Flow and Minimum Cut
- Introduction to Maxflow 00:10:34
- Ford-Fulkerson Algorithm 00:06:33
- Maxflow-Mincut Theorem 00:09:39
- Running Time Analysis 00:08:50
- Java Implementation 00:14:29
- Maxflow Applications 00:22:20

- Lecture 17: Radix Sorts
- Strings in Java 00:17:43
- Key-Indexed Counting 00:12:07
- LSD Radix Sort 00:15:01
- MSD Radix Sort 00:13:42
- 3-way Radix Quicksort 00:07:23
- Suffix Arrays 00:19:25

- Lecture 18: Tries
- R-way Tries 00:32:19
- Ternary Search Tries 00:22:43
- Character-Based Operations 00:20:04

- Lecture 19: Substring Search
- Introduction to Substring Search 00:06:42
- Brute-Force Substring Search 00:10:11
- Knuth-Morris-Pratt 00:33:15
- Boyer-Moore 00:08:37
- Rabin-Karp 00:16:14

- Lecture 20: Regular Expressions
- Regular Expressions 00:20:03
- REs and NFAs 00:13:14
- NFA Simulation 00:18:24
- NFA Construction 00:11:43
- Regular Expression Applications 00:20:06

- Lecture 21: Data Compression
- Introduction to Data Compression 00:22:27
- Run-Length Coding 00:05:59
- Huffman Compression 00:24:15
- LZW Compression 00:27:33

- Lecture 22: Reductions
- Introduction to Reductions 00:09:32
- Designing Algorithms 00:08:13
- Establishing Lower Bounds 00:09:23
- Classifying Problems 00:12:45

- Lecture 23: Linear Programming
- Brewer's Problem 00:21:16
- Simplex Algorithm 00:11:49
- Simplex Implementations 00:16:22
- Linear Programming Reductions 00:11:46

- Lecture 24: Intractability
- Introduction to Intractability 00:17:01
- Search Problems 00:10:57
- P vs. NP 00:16:30
- Classifying Problems 00:13:43
- NP-Completeness 00:12:38
- Coping with Intractability 00:14:02

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