The Ultimate Data Structures & Algorithms: Part 2

5h 56m 46s
English
Paid
May 1, 2024

Data structures and algorithms are patterns for solving problems. Developers who know more about data structures and algorithms are better at solving problems. That’s why companies like Google, Microsoft and Amazon always include interview questions on data structures and algorithms. They want to assess your problem-solving skills. They don't care how many programming languages and frameworks you're familiar with.

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By the end of this course…

You’ll be able to:

  • Ace your next coding interview
  • Write better, faster code
  • Become a better developer
  • Improve your problem solving skills
  • Master computer science fundamentals
  • Implement all the essential data structures from scratch
  • Master dozens of popular algorithms

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# Title Duration
1 Introduction 00:51
2 Introduction 00:56
3 What are Trees 05:37
4 Exercise- Building a Tree 02:42
5 Solution- insert() 07:45
6 Solution- find() 02:01
7 Traversing Trees 05:59
8 Recursion 05:40
9 Depth First Traversals 05:24
10 Depth and Height of Nodes 07:07
11 Minimum Value in a Tree 07:38
12 Exercise- Equality Checking 00:46
13 Solution- Equality Checking 04:09
14 Exercise- Validating Binary Search Trees 04:15
15 Solution- Validating Binary Search Trees 04:19
16 Exercise- Nodes at K Distance 01:49
17 Solution- Nodes at K Distance from the Root 04:38
18 Level Order Traversal 02:56
19 Summary 01:23
20 Introduction 00:32
21 Balanced and Unbalanced Trees 03:02
22 Rotations 05:03
23 AVL Trees 04:05
24 Exercise- Building an AVL Tree 01:12
25 Solution- insert() 08:48
26 Exercise- Height Calculation 01:25
27 Solution- Height Calculation 02:44
28 Exercise- Balance Factor 02:05
29 Solution- Balance Factor 04:02
30 Exercise- Detecting Rotations 02:55
31 Solution- Detecting Rotations 03:34
32 Exercise- Implementing Rotations 03:52
33 Solution- Implementing Rotations 05:41
34 Summary 01:02
35 Introduction 00:22
36 What are Heaps 06:29
37 Exercise- Building a Heap 01:56
38 Solution- insert() 08:25
39 Solution- remove() 07:08
40 Solution - Edge Cases 06:12
41 Heap Sort 02:30
42 Priority Queues 05:05
43 Exercise- Heapify 01:27
44 Solution- Heapify 07:13
45 Solution- Optimization 02:43
46 Exercise- Kth Largest Item 00:32
47 Solution- Kth Largest Item 03:48
48 Summary 01:20
49 Introduction 00:31
50 What are Tries 03:51
51 What are Tries 03:04
52 Solution- Building a Trie 05:45
53 An Implementation with a HashTable 01:51
54 A Better Abstraction 05:29
55 Exercise- Looking Up a Word 01:13
56 Solution- Looking Up a Word 02:36
57 Traversals 03:36
58 Exercise- Removing a Word 01:54
59 Solution- Removing a Word 08:15
60 Exercise- Auto Completion 02:52
61 Solution- Auto Completion 06:00
62 Summary 00:46
63 Introduction 00:27
64 What are Graphs 02:10
65 Adjacency Matrix 04:15
66 Adjacency List 06:33
67 Exercise- Building a Graph 01:51
68 Solution- Adding Nodes and Edges 07:35
69 Solution- Removing Nodes and Edges 04:49
70 Traversal Algorithms 03:59
71 Exercise- Depth-first Traversal (Recursive) 01:30
72 Solution- Depth-first Traversal (Recursive) 03:45
73 Exercise- Depth-first Traversal (Iterative) 02:45
74 Solution- Depth-first Traversal (Iterative) 04:00
75 Exercise- Breadth-first Traversal (Iterative) 01:19
76 Solution- Breadth-first Traversal 02:42
77 Exercise- Topological Sorting 05:07
78 Solution- Topological Sort 04:06
79 Exercise- Cycle Detection (Directed Graphs) 03:43
80 Solution- Cycle Detection (Directed Graphs) 06:27
81 Graphs Summary 01:03
82 Introduction 00:27
83 Exercise- Weighted Graphs 01:31
84 Solution- Weighted Graphs 05:21
85 An Object-oriented Solution 06:14
86 Dijkstra's Shortest Path Algorithm 04:36
87 Exercise- Getting the Shortest Distance 06:09
88 Solution- The Shortest Distance 05:28
89 Solution- Shortest Path 07:54
90 Exercise- Cycle Detection (Undirected Graphs) 02:04
91 Solution- Cycle Detection (Undirected Graphs) 04:43
92 Minimum Spanning Tree 01:57
93 Exercise- Prim's Algorithm 02:46
94 Solution- Prim's Algorithm 10:40

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