The Ultimate Data Structures & Algorithms: Part 2

Name: The Ultimate Data Structures & Algorithms: Part 2
Price: 9 USD
Availability: InStock

5h 56m 46s

English

Paid

May 1, 2024

Course description

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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#1: Introduction

All Course Lessons (94)

#	Lesson Title	Duration
1	Introduction Demo	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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