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    Leetcode In Typescript:Algorithms Coding Interview Questions

    Posted By: ELK1nG
    Leetcode In Typescript:Algorithms Coding Interview Questions

    Leetcode In Typescript:Algorithms Coding Interview Questions
    Published 8/2023
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 5.43 GB | Duration: 22h 33m

    Practice data structure and algorithms questions for interviews at FAANG companies like Google, Facebook, Apple & Amazon

    What you'll learn

    Solve Easy to Hard Difficulty problems using different data structures and algorithms

    How to solve some of the most popular interview questions asked by major tech companies

    Breaking down the coding interview problems in a step by step, systematic manner

    Popular problems patterns

    Algorithms and data structures

    Strengthen your problem solving and programming skills

    Requirements

    Basic Knowledge of fundamental data structures and algorithms is preferred

    Basic Knowledge of typescript is preferred

    If you want to submit the code yourself, you should be familiar with leetcode and have an account

    Description

    Want to master popular problem-solving techniques, data structures, and algorithms that interviewers love? Dive right in!Crave step-by-step explanations for the industry's hottest interview questions? We've got you covered.Looking to up your game in competitive programming? Buckle up for a thrilling journey!Welcome to the course!In this course, you'll have a detailed, step by step explanation of hand-picked LeetCode questions where you'll learn about the most popular techniques and problems used in the coding interview, This is the course I wish I had when I was doing my interviews. and it comes with a 30-day money-back guaranteeWhat is LeetCode?LeetCode is essentially a huge repository of real interview questions asked by the most popular tech companies ( Google, Amazon, Facebook, Microsoft, and more ).The problem with LeetCode is also its advantage, IT'S HUGE, so huge in fact that interviewers from the most popular companies often directly ask questions they find on LeetCode, So it's hard to navigate through the huge amount of problems to find those that really matter, this is what this course is for.I spent countless hours on LeetCode and I'm telling you that you don't have to do the same and still be able to get a job at a major tech company.Course overview :In this course, I compiled the most important and the most popular interview questions asked by these major companies and I explain them, in a true STEP BY STEP fashion to help you understand exactly how to solve these types of questions.The problems are handpicked to ensure complete coverage of the most popular techniques, data structures, and algorithms used in interviews so you can generalise the patterns you learn here on other problems.Each problem gets multiple videos :Explanation video(s): we do a detailed explanation of the problems and its solution, this video will be longer because we will do a step by step explanation for the problems.Coding video(s): where we code the solution discussed in the explanation video together.Walkthrough video(s): where we go over each line of code and see what it doesWe will use basic typescript for this course to code our solutions, previous knowledge in typescript is preferred but NOT required for the coding part of the course.The problems are categorised for easier navigation and will be regularly updated with more popular and interesting problems.Some of the stuff this course will cover are :Arrays and Strings interview questions.Searching interview questions and algorithms.Dynamic Programming interview questions.Backtracking interview questions (  With step by step visualisation ).Trees and Graphs interview questions and algorithms.Data structures Like Stacks, Queues, Maps, Linked Lists, and more.In other words, this course is your one-stop-shop for your dream job.

    Overview

    Section 1: Microsoft Array Question: Container with most water (Medium)

    Lecture 1 Introduction to the problem

    Lecture 2 Brute Force solution Intuition

    Lecture 3 pseudocode walkthrough

    Lecture 4 Better Approach intuition

    Lecture 5 Approach 2 Pseudocode walkthrough

    Lecture 6 Implementing the code

    Section 2: Google Array Question: Valid mountain array (Easy)

    Lecture 7 Introduction to the problem

    Lecture 8 How to think about this problem

    Lecture 9 Pseudocode Walkthrough

    Lecture 10 Implementing the code

    Section 3: Google Array Question: Boats to save people (Medium)

    Lecture 11 Problem Introduction

    Lecture 12 How to intuitively think about this problem

    Lecture 13 Pseudocode Walkthrough

    Lecture 14 Implementing the code

    Section 4: Facebook Array Question: Move Zeroes (Easy)

    Lecture 15 Brute force Intuition

    Lecture 16 Brute force pseudocode walkthrough

    Lecture 17 Better Approach Intuition

    Lecture 18 Better Approach Pseudocode walkthrough

    Lecture 19 Implementing the code

    Section 5: Amazon Array Question: Longest substring without repeating characters (Medium)

    Lecture 20 Introduction to the problem

    Lecture 21 Brute Force Intuition

    Lecture 22 Pseudocode walkthrough

    Lecture 23 Approach 2 Intuition

    Lecture 24 Approach 2 pseudocode walkthrough

    Lecture 25 Implementing the code

    Section 6: Arrays Question:Find first and last position of element in sorted Array (Medium)

    Lecture 26 Introduction to the problem and brute force approach

    Lecture 27 Brute force Pseudocode walkthrough

    Lecture 28 Approach 2: Optimal Approach intuition

    Lecture 29 Pseudocode walkthrough part 1

    Lecture 30 Pseudocode walkthrough part 2

    Lecture 31 Implementing the code

    Section 7: Google Array question: first bad version (Easy)

    Lecture 32 Introduction To The Problem And Brute Force Approach

    Lecture 33 Optimal Solution Intuition

    Lecture 34 Optimal solution pseudocode walkthrough

    Lecture 35 Implementing the code

    Section 8: Microsoft Math Question: Missing Number (Easy-ish)

    Lecture 36 Introduction to the problem

    Lecture 37 Approach 1: Brute Force Approach

    Lecture 38 Approach 2: A Better Approach Explanation

    Lecture 39 PseudoCode Walkthrough For Approach 2

    Lecture 40 Implementing the code

    Lecture 41 Approach 3: Optimal Approach

    Lecture 42 Implementing the optimal approach

    Section 9: Amazon Math Question: Count Primes

    Lecture 43 Problem Introduction And Brute Force Explanation

    Lecture 44 Pseudocode Walkthrough For Brute Force Approach

    Lecture 45 Approach 2: Optimal solution

    Lecture 46 Pseudocode Walkthrough For Optimal Approach

    Lecture 47 Code Implementation

    Section 10: Airbnb Math Question: Single Number

    Lecture 48 Introduction to the problem and brute force approach

    Lecture 49 Pseudocode walkthrough for brute approach

    Lecture 50 Approach 2: better Approach

    Lecture 51 Implementing the code

    Lecture 52 Approach 3: optimal approach

    Lecture 53 Implementing the optimal approach

    Section 11: Amazon Math Question: Robot return to origin (Easy)

    Lecture 54 Explaining the problem

    Lecture 55 Implementing the code

    Section 12: Facebook Math Question: Add Binary (Easy)

    Lecture 56 Introduction to the problem

    Lecture 57 Examples of binary additions

    Lecture 58 Pseudocode Implementation

    Lecture 59 Pseudocode Walkthrough

    Lecture 60 Implementing the code

    Section 13: Google Hash Tables / Dictionaries question: Two Sum (Easy)

    Lecture 61 Approach 1: Introduction to the problem and brute force approach

    Lecture 62 Brute force Pseudocode Implementation

    Lecture 63 Pseudocode Walkthrough

    Lecture 64 Approach 2: Optimal Approach Explanation

    Lecture 65 Pseudocode Walkthrough

    Lecture 66 Code Implementation

    Section 14: Google Hash Tables / Dictionaries question: Contains Duplicate

    Lecture 67 Introduction to the problem and multiple approaches

    Lecture 68 Optimal Approach

    Lecture 69 Code Implementation

    Section 15: Google Hash Tables / Dictionaries question: Majority Element

    Lecture 70 Approach 1 Intuition

    Lecture 71 Approach 1 Pseudocode Walkthrough

    Lecture 72 Approach 2 - Majority Element Intuition

    Lecture 73 Implementing Approach 2 code

    Lecture 74 Approach 3 Intuition - Optimal solution

    Lecture 75 Approach 3 Walkthrough - Optimal solution

    Lecture 76 Implementing Approach 3 (optimal approach)

    Section 16: Facebook Hash Tables / Dictionaries question: Group Anagrams (Medium)

    Lecture 77 Explanation - Group Anagrams - Medium #49

    Lecture 78 Code - Group Anagrams - Medium #49

    Section 17: Hash Tables / Dictionaries question: 4sum 2 (Medium)

    Lecture 79 Brute force Explanation

    Lecture 80 Brute Force Pseudocode Walkthrough

    Lecture 81 Approach 2: Optimal approach

    Lecture 82 Implementing the code

    Section 18: Microsoft Hash Tables / Dictionaries question: LRU Cache (Medium)

    Lecture 83 Introduction to the problem

    Lecture 84 Input/Ouput for the problem

    Lecture 85 Intuition behind the problem

    Lecture 86 Pseudocode implementation

    Lecture 87 Pseudocode Walkthrough

    Section 19: Linkedin Hash Tables / Dictionaries question: Minimum Window Substring (Hard)

    Lecture 88 Explanation - Minimum Window Substring - part 1

    Lecture 89 Explanation - Minimum window substring - part 2

    Lecture 90 Explanation - Minimum window substring - part 3

    Lecture 91 Pseudocode Implementation

    Lecture 92 Pseudocode Walkthrough

    Lecture 93 Code - Minimum Window Substring - Hard #76

    Section 20: Apple Linked list question: Merge Two Sorted Lists (Easy)

    Lecture 94 Explanation - Merge Two Sorted Lists - Easy #21

    Lecture 95 Implementation - Merge Two Sorted Lists - Easy #21

    Lecture 96 Walkthrough - Merge Two Sorted Lists - Easy #21

    Lecture 97 Code - Merge Two Sorted Lists - Easy #21

    Section 21: Amazon Linked list question: Linked list cycle (Medium)

    Lecture 98 Explanation - Linked List Cycle - Easy #141

    Lecture 99 Intuition - Linked List Cycle - Easy #141

    Lecture 100 Walkthrough - Linked List Cycle - Easy #141

    Lecture 101 Code - Linked List Cycle - Easy #141

    Section 22: Microsoft Linked list question: Reverse linked list (Medium)

    Lecture 102 Explanation - Reverse Linked List

    Lecture 103 Intuition - Reverse Linked List

    Lecture 104 pseudocode Implementation & Walkthrough - Reverse Linked List

    Lecture 105 Implementing the code - Reverse Linked List

    Section 23: Adobe Linked list question: Add two numbers (Medium)

    Lecture 106 Explanation - Add Two Numbers

    Lecture 107 Intuition - Add Two Numbers

    Lecture 108 Pseudocode Implementation - Add Two Numbers

    Lecture 109 Walkthrough - Add Two Numbers - Medium #2

    Lecture 110 Code - Add Two Numbers

    Section 24: Linked list question: Remove Nth node from end of list (Medium)

    Lecture 111 Explanation - Remove Nth Node From End of List

    Lecture 112 Intuition - Remove Nth Node From End of List

    Lecture 113 Walkthrough - Remove Nth Node From End of List

    Lecture 114 Approach 2 Explanation - Remove Nth Node From End of List

    Lecture 115 Approach 2 Walkthrough - Remove Nth Node From End of List - Medium #19

    Lecture 116 Code - Remove Nth Node From End of List

    Section 25: Linked list question: Odd Even linked list (Medium)

    Lecture 117 Explanation - Odd Even Linked List

    Lecture 118 Intuition - Odd Even Linked List

    Lecture 119 Pseudocode Implementation - Odd Even Linked List

    Lecture 120 Walkthrough - Odd Even Linked List

    Lecture 121 Code - Odd Even Linked List

    Section 26: Google Linked list question: Merge K sorted lists (Hard)

    Lecture 122 Explanation - Merge K Sorted Lists - Hard #23

    Section 27: Facebook Backtracking question: Subsets (Medium)

    Lecture 123 Explanation - Subsets

    Lecture 124 Cascading solution explanation - Subsets

    Lecture 125 Cascading solution walkthrough - Subsets

    Lecture 126 Backtracking Approach 2 explanation - Subsets

    Lecture 127 Implementing the code

    Section 28: Amazon Backtracking question: Letter Combination of a Phone Number (Medium)

    Lecture 128 Explanation - Letter Combinations of a Phone Number

    Lecture 129 Intuition - Letter Combinations of a Phone Number

    Lecture 130 Walkthrough - Letter Combinations of a Phone Number

    Lecture 131 Code - Letter Combinations of a Phone Number

    Section 29: Uber Backtracking question: Combination Sum (Medium)

    Lecture 132 Explanation the problem

    Lecture 133 Intuition behind the problem

    Lecture 134 Walkthrough over the pseudocode

    Lecture 135 Implementing the code

    Section 30: Bloomberg Backtracking question: Palindrome Partitioning (Medium)

    Lecture 136 Intuition behind the problem

    Lecture 137 Pseudocode implementation

    Lecture 138 Walkthrough over pseudocode

    Lecture 139 Implementing the code

    Section 31: Microsoft Trees question: Symmetric Trees (Easy)

    Lecture 140 Explaining the problem

    Lecture 141 Intuition behind the problem

    Lecture 142 Walkthrough over pseudocode

    Lecture 143 Implementing the code

    Section 32: Google Trees question: Maximum Depth of a Binary Tree (Easy)

    Lecture 144 Explaining the problem

    Lecture 145 Intuition and pseudocode implementation

    Lecture 146 Walkthrough over pseudocode

    Lecture 147 Implementing the code

    Section 33: Amazon Trees question: Path Sum (Easy)

    Lecture 148 Explaining the problem

    Lecture 149 Intuition behind the problem

    Lecture 150 Walkthrough over pseudocode

    Lecture 151 Coding the solution

    Section 34: Facebook Trees question: Lowest Common Ancestor of a Binary Tree (Medium)

    Lecture 152 Explaining the problem

    Lecture 153 Intuition behind the problem

    Lecture 154 Pseudocode implementation

    Lecture 155 Walkthrough over pseudocode

    Section 35: Google Trees question: Kth Smallest Element In a BST (Medium)

    Lecture 156 Explaining the problem

    Lecture 157 Optimized Solution Explanation- Kth Smallest Element in a BST - Medium #230

    Lecture 158 Code - Kth Smallest Element in a BST - Medium #230

    Section 36: Microsoft Trees question: Serialise And Deserialise Binary Tree (Hard)

    Lecture 159 Explaining the "Serialisation"

    Lecture 160 Walkthrough over pseudocode (Serialisation)

    Lecture 161 Explaining the "Deserialisation"

    Lecture 162 Walkthrough over pseudocode (Deserialisation)

    Section 37: Microsoft Trees question: Binary Tree Maximum Path Sum (Hard)

    Lecture 163 Explaining the problem

    Lecture 164 Intuition behind the problem

    Lecture 165 Walkthrough over pseudocode

    Lecture 166 Coding the solution

    Section 38: Google Stack Question: Min Stack (Easy)

    Lecture 167 Brute force explanation - Min Stack - Easy #155

    Lecture 168 Walkthrough over pseudocode

    Lecture 169 Optimal solution explanation

    Section 39: Amazon Stack Question: Valid Parenthesis (Easy)

    Lecture 170 Explaining the problem

    Lecture 171 Intuition behind this problem

    Lecture 172 Pseudocode Implementation

    Lecture 173 Walkthrough over the pseudocode

    Lecture 174 Code - Valid Parenthesis - Easy #20

    Section 40: Apple Stack Question: Binary Tree Level Order Traversal (Medium)

    Lecture 175 Explaining the problem

    Lecture 176 Walkthrough over pseudocode

    Lecture 177 Implementing the code

    Section 41: Microsoft Queue Question: Binary Tree Zigzag Level Order Traversal (Medium)

    Lecture 178 Explaining the problem

    Lecture 179 Intuition behind the problem

    Lecture 180 Walkthrough over pseudocode

    Lecture 181 Optimal solution explanation

    Lecture 182 Optimal solution pseudocode walkthrough

    Lecture 183 Implementing the code

    Section 42: Stack Question: Binary Tree Postorder Traversal (Medium)

    Lecture 184 Explanation of the problem

    Lecture 185 Implementing the code

    Section 43: Google Dynamic Programming Question: House Robber (Easy)

    Lecture 186 Explanation behind the problem

    Lecture 187 Intuition behind the problem

    Lecture 188 2nd Approach: Bottom Up dynamic programming

    Lecture 189 Walkthrough behind pseudocode

    Lecture 190 Implementing the code

    Section 44: Facebook Dynamic Programming Question: Best Time To Buy And Sell Stocks (Easy)

    Lecture 191 Explanation behind the problem

    Lecture 192 Intuition behind the problem

    Lecture 193 Walkthrough over pseudocode

    Lecture 194 Optimal solution explanation

    Lecture 195 Coding the solution

    Section 45: Amazon Dynamic Programming Question: Climbing Stairs (Easy)

    Lecture 196 Explaining the problem

    Lecture 197 Intuition behind the problem

    Lecture 198 Implementation the pseudocode

    Lecture 199 Bottom up approach explanation

    Lecture 200 Bottom up approach walkthrough - Climbing Stairs - Easy #70

    Lecture 201 Bottom up optimization - Climbing Stairs - Easy #70

    Lecture 202 Code - Climbing Stairs - Easy #70

    Section 46: Google Dynamic Programming Question: Coin Change (Medium)

    Lecture 203 Explaining the problem

    Lecture 204 Intuition behind the problem

    Lecture 205 Pseudocode Implementation and optimisation

    Lecture 206 Bottom up approach explanation

    Section 47: Bloomberg Dynamic Programming Question: Unique Paths (Medium)

    Lecture 207 Explaining the problem

    Lecture 208 Pseudocode Implementation and walkthrough

    Lecture 209 Implementing the code

    Section 48: Microsoft Dynamic Programming Question: Longest Palindromic Substring (Medium)

    Lecture 210 Explanation of the problem

    Lecture 211 Initial Intuition behind the problem

    Lecture 212 Optimising the previous solution

    Lecture 213 Pseudocode Implementation

    Lecture 214 Walkthrough over pseudocode

    Lecture 215 Implementing the code

    Section 49: Amazon Dynamic Programming Question: Trapping Rain Water (Hard)

    Lecture 216 Explaining the problem

    Lecture 217 coding the implementation

    Developers eager to pass the coding interview at huge companies like Google, Facebook, Microsoft, Amazon, etc.,People who want to develop their problem solving skills.,Developers getting ready for their technical interviews.,Students getting ready for their internship coding interviews.,People who want to get better at competitive coding