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The Ultimate Data Structures & Algorithms: Part 2
Getting Started
1- Introduction (0:50)
2- Source Code
3- Follow Me Around
4- Learning Paths
Binary Trees (73m)
1- Introduction (0:55)
2- What are Trees (5:36)
3- Exercise- Populating a Binary Search Tree
4- Exercise- Building a Tree (2:41)
5- Solution- insert() (7:44)
6- Solution- find() (2:00)
7- Traversing Trees (5:58)
8- Exercise- Tree Traversal
9- Recursion (5:39)
10- Depth First Traversals (5:23)
11- Depth and Height of Nodes (7:06)
12- Minimum Value in a Tree (7:37)
13- Exercise- Equality Checking (0:45)
14- Solution- Equality Checking (4:08)
15- Exercise- Validating Binary Search Trees (4:14)
16- Solution- Validating Binary Search Trees (4:18)
17- Exercise- Nodes at K Distance (1:48)
18- Solution- Nodes at K Distance from the Root (4:37)
19- Level Order Traversal (2:55)
20- Trees- Exercises
21- Summary (1:22)
AVL Trees (49m)
1- Introduction (0:31)
2- Balanced and Unbalanced Trees (3:01)
3- Rotations (5:02)
4- AVL Trees (4:04)
5- Exercise: AVL Rotations
6- Exercise- Building an AVL Tree (1:11)
7- Solution- insert() (8:47)
8- Exercise- Height Calculation (1:24)
9- Solution- Height Calculation (2:43)
10- Exercise- Balance Factor (2:04)
11- Solution- Balance Factor (4:01)
12- Exercise- Detecting Rotations (2:54)
13- Solution- Detecting Rotations (3:32)
14- Exercise- Implementing Rotations (3:51)
15- Solution- Implementing Rotations (5:40)
16- AVL Trees- Exercises
17- Summary (1:01)
A Quick Note
Heaps (53m)
1- Introduction (0:21)
2- What are Heaps (6:28)
3- Exercise- Working with Heaps
4- Exercise- Building a Heap (1:55)
5- Solution- insert() (8:24)
6- Solution- remove() (7:07)
7- Solution - Edge Cases (6:11)
8- Heap Sort (2:29)
9- Priority Queues (5:04)
10- Exercise- Heapify (1:26)
11- Solution- Heapify (7:12)
12- Solution- Optimization (2:42)
13- Exercise- Kth Largest Item (0:31)
14- Solution- Kth Largest Item (3:47)
15- Heaps- Exercises
16- Summary (1:19)
Tries (46m)
1- Introduction (0:30)
2- What are Tries (3:50)
3- Exercise- Populating a Trie
4- Exercise- Building a Trie (3:03)
5- Solution- Building a Trie (5:44)
6- An Implementation with a HashTable (1:50)
7- A Better Abstraction (5:28)
8- Exercise- Looking Up a Word (1:12)
9- Solution- Looking Up a Word (2:35)
10- Traversals (3:35)
11- Exercise- Removing a Word (1:53)
12- Solution- Removing a Word (8:14)
13- Exercise- Auto Completion (2:51)
14- Solution- Auto Completion (5:59)
15- Tries- Exercises
16- Summary (0:45)
A Quick Note
Graphs (66m)
1- Introduction (0:26)
2- What are Graphs (2:09)
3- Adjacency Matrix (4:14)
4- Adjacency List (6:32)
5- Exercise- Building a Graph (1:50)
6- Solution- Adding Nodes and Edges (7:34)
7- Solution- Removing Nodes and Edges (4:48)
8- Traversal Algorithms (3:58)
9- Exercise- Traversal Algorithms
10- Exercise- Depth-first Traversal (Recursive) (1:29)
11- Solution- Depth-first Traversal (Recursive) (3:44)
12- Exercise- Depth-first Traversal (Iterative) (2:44)
13- Solution- Depth-first Traversal (Iterative) (3:59)
14- Exercise- Breadth-first Traversal (Iterative) (1:18)
15- Solution- Breadth-first Traversal (2:41)
16- Exercise- Topological Sorting (5:06)
17- Solution- Topological Sort (4:05)
18- Exercise- Cycle Detection (Directed Graphs) (3:42)
19- Solution- Cycle Detection (Directed Graphs) (6:26)
20- Graphs Summary (1:02)
Undirected Graphs (59m)
1- Introduction (0:26)
2- Exercise- Weighted Graphs (1:30)
3- Solution- Weighted Graphs (5:20)
4- An Object-oriented Solution (6:13)
5- Dijkstra's Shortest Path Algorithm (4:35)
6- Exercise- Getting the Shortest Distance (6:08)
7- Solution- The Shortest Distance (5:27)
8- Solution- Shortest Path (7:53)
9- Exercise- Cycle Detection (Undirected Graphs) (2:03)
10- Solution- Cycle Detection (Undirected Graphs) (4:42)
11- Minimum Spanning Tree (1:56)
12- Exercise- Prim's Algorithm (2:45)
13- Solution- Prim's Algorithm (10:39)
14- Course Wrap Up (0:30)
15- Thank You
18- Solution- Nodes at K Distance from the Root
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