# Master the Coding Interview: Data Structures + Algorithms

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 261 Lessons (19h 40m) | 5.60 GB

The ultimate coding interview bootcamp to help you ace your coding interviews and land your dream job. You’ll not only learn data structures and algorithms but also the exact steps to take to get more interviews, more job offers, and a higher salary.

Completely updated for 2022! We guarantee you that this is the best coding interview bootcamp that you can find if you are serious about learning data structures & algorithms, want to make up for not having a Computer Science Degree, and want to get hired as a Developer at the company of your dreams.

WHAT YOU’LL LEARN

• Ace coding interviews given by some of the top tech companies
• Learn to implement and use different Data Structures
• Learn to implement and use different Algorithms
• Learn the notorious Big-O notation
• Become a better developer by mastering computer science fundamentals
• Learn from a Senior Programmer who has managed teams of engineers and has been in these interviews both as the interviewee and interviewer
• Get more interviews and more job offers
• Become more confident and prepared for your next coding interview
• Professionally handle offers and negotiate raises

Introduction
1 How To Succeed In This Course
3 Exercise Meet Your Classmates and Instructor
4 Monthly Coding Challenges, Free Resources and Guides

Getting More Interviews
5 Section Overview
6 Resume
7 Exercise Resume Walkthrough
8 Resume Review
9 Resources Resume Templates
10 What If I Don’t Have Enough Experience
11 Optional Exercise Github Master
14 Portfolio
15 Resources Free Portfolio Templates
16 Email
17 Resources Email
18 Where To Find Jobs
19 Resources Where To Find Jobs
20 When Should You Start Applying
21 Section Summary

Big O
24 Section Overview
25 Python, Java, CC++, C#, Golang, Swift, Kotlin, TypeScript, + Perl Solutions!
26 Big O Cheatsheet
27 What Is Good Code
28 Big O and Scalability
29 O(n)
30 O(1)
31 Exercise Big O Calculation
32 Solution Big O Calculation
33 Exercise Big O Calculation 2
34 Solution Big O Calculation 2
35 Simplifying Big O
36 Big O Rule 1
37 Big O Rule 2
38 Big O Rule 3
39 O(n^2)
40 Big O Rule 4
41 Big O Cheat Sheet
42 What Does This All Mean
43 O(n!)
44 Pillars Of Programming
45 Space Complexity
46 Exercise Space Complexity
48 Optional Javascript Loops
49 Section Summary

How To Solve Coding Problems
50 Section Overview
51 What Are Companies Looking For
52 What We Need For Coding Interviews
54 Exercise Interview Question
55 Exercise Interview Question 2
58 Section Summary

Data Structures Introduction
59 Section Overview
60 What Is A Data Structure
61 How Computers Store Data
62 Data Structures In Different Languages
63 Operations On Data Structures

Data Structures Arrays
64 Arrays Introduction
65 Static vs Dynamic Arrays
66 Quick Note Upcoming Video
67 Optional Classes In Javascript
68 Implementing An Array
69 Strings and Arrays
70 Exercise Reverse A String
71 Solution Reverse A String
72 Exercise Merge Sorted Arrays
73 Solution Merge Sorted Arrays
74 Interview Questions Arrays
75 Arrays Review

Data Structures Hash Tables
76 Hash Tables Introduction
77 Hash Function
78 Hash Collisions
79 Hash Tables In Different Languages
80 Exercise Implement A Hash Table
81 Solution Implement A Hash Table
82 keys()
83 Extra keys() Without Collision
84 Hash Tables VS Arrays
85 Exercise First Recurring Character
86 Solution First Recurring Character
87 Interesting Tidbit Python Dictionaries
88 Hash Tables Review

90 What Is A Linked List
91 Exercise Imposter Syndrome
94 What Is A Pointer
96 Solution append()
97 Solution prepend()
98 Node Class
99 insert()
100 Quick Note Upcoming Video
101 Solution insert()
102 Solution remove()
106 Singly VS Doubly Linked Lists
107 Exercise reverse()
108 Solution reverse()

Data Structures Stacks + Queues
110 Stacks + Queues Introduction
111 Stacks
112 Queues
113 Exercise Stacks VS Queues
114 Solution Stacks VS Queues
115 Quick Note Upcoming Video
116 Optional How Javascript Works
117 Exercise Stack Implementation (Linked Lists)
118 Solution Stack Implementation (Linked Lists)
119 Exercise Stack Implementation (Array)
120 Solution Stack Implementation (Array)
121 Exercise Queue Implementation
122 Solution Queue Implementation
123 Queues Using Stacks
124 Stacks + Queues Review

Data Structures Trees
125 Trees Introduction
126 Binary Trees
127 O(log n)
128 Binary Search Trees
129 Balanced VS Unbalanced BST
130 BST Pros and Cons
131 Exercise Binary Search Tree
132 Solution insert()
133 Solution lookup()
134 Extra Exercise remove()
135 Solution remove()
136 AVL Trees + Red Black Trees
137 Resources AVL Trees + Red Black Trees
138 Binary Heaps
139 Quick Note on Heaps
140 Priority Queue
141 Trie
142 Tree Review

Data Structures Graphs
143 Graphs Introduction
144 Types Of Graphs
145 Exercise Guess The Graph
146 Graph Data
147 Exercise Graph Implementation
148 Solution Graph Implementation
149 Graphs Review
150 Data Structures Review
151 What Else Is Coming Up

Algorithms Recursion
152 Introduction to Algorithms
153 Recursion Introduction
154 Stack Overflow
155 Anatomy Of Recursion
156 Exercise Factorial
157 Solution Factorial
158 Exercise Fibonacci
159 Solution Fibonacci
160 Recursive VS Iterative
161 When To Use Recursion
162 Exercise Reverse String With Recursion
163 Recursion Review

Algorithms Sorting
164 Sorting Introduction
165 The Issue With sort()
166 Sorting Algorithms
167 Bubble Sort
168 Exercise Bubble Sort
169 Solution Bubble Sort
170 Selection Sort
171 Exercise Selection Sort
172 Solution Selection Sort
173 Dancing Algorithms
174 Insertion Sort
175 Exercise Insertion Sort
176 Solution Insertion Sort
177 Merge Sort and O(n log n)
178 Exercise Merge Sort
179 Solution Merge Sort
180 Stable VS Unstable Algorithms
181 Quick Sort
182 Optional Exercise Quick Sort
183 Which Sort Is Best
184 Resources Heap Sort
185 Radix Sort + Counting Sort
186 Resources Radix Sort + Counting Sort
187 Exercise Sorting Interview
188 Solution Sorting Interview
190 Sorting Review

Algorithms Searching + BFS + DFS
191 Searching + Traversal Introduction
192 Linear Search
193 Binary Search
194 Graph + Tree Traversals
195 BFS Introduction
196 DFS Introduction
197 BFS vs DFS
198 Resources BFS vs DFS
199 Exercise BFS vs DFS
200 Solution BFS vs DFS
203 PreOrder, InOrder, PostOrder
204 depthFirstSearch()
205 Optional Exercise Validate A BST
206 Graph Traversals
207 BFS in Graphs
208 DFS in Graphs
209 Dijkstra + Bellman-Ford Algorithms
210 Searching + Traversal Review

Algorithms Dynamic Programming
211 Dynamic Programming Introduction
212 Memoization 1
213 Memoization 2
214 Fibonacci and Dynamic Programming
215 Dynamic Programming
216 Implementing Dynamic Programming
217 Interview Questions Dynamic Programming
218 Dynamic Programming Review

Non Technical Interviews
219 Section Overview
220 During The Interview
221 Exercise Hero Stories
224 Why Us
225 Tell Me About A Problem You Have Solved
226 Exercise Past Projects
227 What Is Your Biggest Weakness
229 Any Questions For Us
230 Resources Questions To Ask A Company
231 Secret Weapon
232 After The Interview
233 Section Summary

Offer + Negotiation
234 Section Overview
235 Handling Rejection
236 Negotiation 101
237 Handling An Offer
238 Handling Multiple Offers
239 Getting A Raise
240 Exercise Negotiation Master
241 Section Summary

Thank You
242 Become an Alumni
243 Thank You
244 What You Can Do Now

245 Coding Problems
246 Top Interview Questions
247 Amazon Interview Questions
250 Domain Specific Questions

Contributing To Open Source To Gain Experience
251 Contributing To Open Source
252 Contributing To Open Source 2
253 Exercise Contribute To Open Source

Extra Bits
254 Learning Guideline
255 Quick Note Upcoming Videos
256 From JTS Learn to Learn