1 S01 - L01 -- Course Breakdown Demo 07:09 2 S01 - L02 -- What is DS and Algo 04:37 3 S01 - L03 -- Why companies ask DS 03:28 4 S01 - L04 -- DS in every day life 03:30 5 03:42 6 S01.1-L01--What is Recursion 11:59 7 S01.1-L02--Why learn Recursion 05:07 8 S01.1-L03--Format of Recursion Method 04:09 9 S01.1-L04--How Recurssion works internally 14:41 10 S01.1-L05--Finding Factorial using Recursion 08:22 11 S01.1-L06--Finding Fibonacci using Recursion 07:42 12 S01.1-L07--Recursion vs Iteration 03:19 13 S01.1-L08--When to Use & Avoid Recursion 04:43 14 S01.1-L09--Practical Uses of Recursion 03:16 15 S02-L01 -- What is Algo Run Time Analysis 03:14 16 S02-L02 -- What are Notations 10:39 17 S02-L03 -- Examples of Notations 07:55 18 S02-L04 -- Examples of Time Complexity 06:52 19 S02-L05 -- Finding Time Complexity of Iterative Algo 08:14 20 S02-L06 -- Finding Time Complexity of Recursive Algo#1 11:10 21 S02-L07 -- Finding Time Complexity of Recursive Algo#2 17:48 22 S03 - L01 -- What and Why of Array 07:02 23 S03 - L02 -- Types of Array 07:18 24 S03 - L03 -- How is Array represented in Memory 06:01 25 S03 - L04 -- Create an Array 11:26 26 S03 - L05 -- Insert Traverse in 1D Array 07:05 27 S03 - L06 -- Access Search Delete in 1D Array 16:27 28 S03 - L07 -- Code 1D Array 13:45 29 S03 - L08 -- Time Complexity of 1D Array 04:02 30 S03 - L09 -- Create 2D Array 09:14 31 S03 - L10 -- 2D Array operations 14:49 32 S03 - L11 -- Time Complexity of 2D Array 02:56 33 S03 - L12 -- When to use Array 06:17 34 S03 - L13 -- Code 2D Array 14:33 35 S03 - L14 -- Practical uses of Array 07:31 36 S04 - L01 -- What is linked list 08:44 37 S04 - L02 -- Linked list vs Array 03:19 38 S04 - L03 -- Components of LinkedList 06:30 39 S04 - L04 -- Types of LinkedList 06:55 40 S04 - L05 -- Why so many types of LinkedList 07:57 41 S04 - L06 -- How is LinkedList stored in Memory 05:06 42 S04 - L07 -- Creation of Single LinkedList (SLL) 05:57 43 S04 - L08 -- Insertion in SLL - Dry Run 07:24 44 S04 - L09 -- Insertion in SLL - Algo 10:57 45 S04 - L10 -- Traversal of SLL 03:50 46 S04 - L11 -- Search node in SLL 04:53 47 S04 - L12 -- Deletion of node from SLL - Dry Run 09:14 48 S04 - L13 -- Deletion of node from SLL - Algo 08:48 49 S04 - L14 -- Delete entire SLL 03:15 50 S04 - L15 -- Time Complexity of SLL 03:30 51 S04 - L16 -- Creation of Circular Single LinkedList (CSLL) 04:07 52 S04 - L17 -- Insertion of data in CSLL - Dry Run 06:16 53 S04 - L18 -- Insertion of data in CSLL - Algo 07:45 54 S04 - L19 -- Traverse CSLL 02:31 55 S04 - L20 -- Search a node in CSLL 04:54 56 S04 - L21 -- Delete a node from CSLL - Dry Run 05:35 57 S04 - L22 -- Deletion of node from CSLL - Algo 07:05 58 S04 - L23 -- Deletion of entire CSLL 04:02 59 S04 - L24 -- Time Complexity of CSLL 04:17 60 S04 - L25 -- Create Double Linked List (DLL) 05:59 61 S04 - L26 -- Insert node in DLL - Dry Run 08:00 62 S04 - L27 -- Insert node in DLL - Algo 13:35 63 S04 - L28 -- Traverse DLL 02:32 64 S04 - L29 -- Reverse Traversal of DLL 03:21 65 S04 - L30 -- Search a node in DLL 03:13 66 S04 - L31 -- Delete a node from DLL - Dry Run 07:21 67 S04 - L32 -- Delete a node from DLL - Algo 09:40 68 S04 - L33 -- Delete entire DLL 04:47 69 S04 - L34 -- Time Complexity of DLL 04:13 70 S04 - L35 -- Create Double Circular LinkedList (CDLL) 07:37 71 S04 - L36 -- Insert node in CDLL - Dry Run 11:06 72 S04 - L37 -- Insert node in CDLL - Algo 09:46 73 S04 - L38 -- Traverse CDLL 03:36 74 S04 - L39 -- Reverse traverse CDLL 03:28 75 S04 - L40 -- Search a node in CDLL 04:31 76 S04 - L41 -- Delete a node from CDLL - Dry Run 08:45 77 S04 - L42 -- Delete a node from CDLL - Algo 10:38 78 S04 - L43 -- Delete entire CDLL 06:29 79 S04 - L44 -- Time Complexity of CDLL 04:27 80 S04 - L45 -- SLL vs CSLL vs DLL vs DLL 06:43 81 S04 - L46 -- Practical uses of LinkedList 05:10 82 L01 -- What and Why of Stack 04:55 83 L02 -- ARRAY - Create & Push 06:19 84 L03 -- ARRAY - Pop, Peek, isEmpty, isFull, Delete 07:52 85 L04 -- LinkedList - Create, Push, Pop 06:36 86 L05 -- LinkedList - Peek, Delete 05:06 87 L06 -- When to use or avoid Stack 03:36 88 S06 - L01 -- What and Why of Queue 03:53 89 S06 - L02 -- LINEAR QUEUE(Array) - Create, Enqueue 06:59 90 S06 - L03 -- LINEAR QUEUE((Array)) - deQueue, isEmpty, isFull, Delete 07:23 91 S06 - L04 -- Why Circular Queue 04:45 92 S06 - L05 -- CIRCULAR QUEUE(Array) - Enqueue 05:57 93 S06 - L06 -- CIRCULAR QUEUE(Array) - Dequeue 03:19 94 S06 - L07 -- CIRCULAR QUEUE(Array) - Peek, isEmpty, isFull, Delete 05:22 95 S06 - L08 -- LINEAR QUEUE(LL) - Enqueue 05:31 96 S06 - L09 -- LINEAR QUEUE(LL) - DeQueue 03:11 97 S06 - L10 -- LINEAR QUEUE(LL) - Peek, isEmpty, Delete 04:04 98 S06 - L11 -- Array vs LinkedList Implementation 04:29 99 S08.01 - L01 -- What is Tree 09:30 100 S08.01 - L02 -- Why learn Tree 02:08 101 S08.01 - L03 -- Tree Terminologies - Part#1 10:01 102 S08.01 - L03 -- Tree Terminologies - Part#2 04:29 103 S08.01 - L04 -- What & Why of Binary Ttree 04:15 104 S08.01 - L05 -- Types of Binary Tree 05:29 105 S08.01 - L06 -- How is Tree Represented in Code 08:54 106 S08.01 - L07 -- Create blank Binary Tree(LL) 03:17 107 S08.01 - L08 -- Pre-order traversal Binary Tree(LL) 14:45 108 S08.01 - L09 -- In-order traversal Binary Tree(LL) 06:18 109 S08.01 - L10 -- Post-order traversal Binary Tree(LL) 06:33 110 S08.01 - L11 -- Level-order traversal Binary Tree(LL) 07:26 111 S08.01 - L12 -- Search for value in Binary Tree(LL) 08:10 112 S08.01 - L13 -- Insert value in Binary Tree(LL) 05:54 113 S08.01 - L14 -- Delete value from Binary Tree(LL) 06:55 114 S08.01 - L15 -- Delete Binary Tree(LL) 03:59 115 S08.01 - L16 -- Create Binary Tree(Array) 05:14 116 S08.01 - L17 -- Insert value in Binary Tree(Array) 05:55 117 S08.01 - L18 -- Search for value in Binary Tree(Array) 03:39 118 S08.01 - L19 -- Inorder traversal of Binary Tree(Array) 06:18 119 S08.01 - L20 -- Pre-order traversal of Binary Tree(Array) 03:48 120 S08.01 - L21 -- Post-order traversal of Binary Tree(Array) 04:18 121 S08.01 - L22 -- Level-order traversal of Binary Tree(Array) 02:46 122 S08.01 - L23 -- Delete node from Binary Tree(Array) 05:34 123 S08.01 - L24 -- Delete Binary Tree(Array) 03:26 124 S08.01 - L25 -- Binary Tree (Array vs Linked List) 04:44 125 S08.02 - L01 -- What & Why of BST 04:45 126 S08.02 - L02 -- Creation & Searching in BST 10:00 127 S08.02 - L03 -- Traversing a BST 07:37 128 S08.02 - L04 -- Inserting a node in BST 13:58 129 S08.02 - L05 -- Deleting a node from BST 15:55 130 S08.02 - L06 -- Deleting a BST 03:43 131 S08.03 - L01 -- Why learn AVL Tree 06:49 132 S08.03 - L02 -- What is AVL Tree 10:21 133 S08.03 - L03 -- Create Search Traverse AVL Tree 06:28 134 S08.03 - L04 -- Insert in AVL_LL Theory 12:02 135 S08.03 - L05 -- Insert in AVL_LL Algorithm 04:48 136 S08.03 - L06 -- Insert in AVL LR 08:13 137 S08.03 - L07 -- Insert in AVL RR 08:24 138 S08.03 - L08 -- Insert in AVL RL 06:23 139 S08.03 - L09 -- Insert End to End Case 14:20 140 S08.03 - L10 -- Delete LL LR RR RL 11:27 141 S08.03 - L11 -- Delete End to End Case 11:57 142 S08.03 - L12 -- Delete AVL Tree & Tree Comparison 07:37 143 S08.04 - L01 -- What Why and Type of Heap 12:27 144 S08.04 - L02 -- Create, Peek, Size of Heap 04:45 145 S08.04 - L03 -- Insert element in Heap 05:12 146 S08.04 - L04 -- Extract and Delete from Heap 06:04 147 S08.04 - L05 -- Why avoid Reference based implementation ? 03:50 148 S08.05 - L01 -- What and Why of Trie 05:57 149 S08.05 - L02 -- Create Insert in Trie 06:53 150 S08.05 - L03 -- Search a String in Trie 02:36 151 S08.05 - L04 -- Delete a String from Trie 07:38 152 S08.05 - L05 -- Practical Uses of Trie 02:33 153 S09 - L01 -- Introduction to Hashing 03:39 154 S09 - L02 -- Why learn Hashing ? 05:13 155 S09 - L03 -- Introduction to Hash Functions 08:53 156 S09 - L04 -- Types of Collision Resolution Techniques 14:55 157 S09 - L05 -- What happens when Hash Table is full ? 04:31 158 S09 - L06 -- Collision Resolution Techniques Compared 08:27 159 S09 - L07 -- Practical Use of Hashing 06:41 160 S09 - L08 -- Hashing vs Other DS 04:37 161 S10 - L01 -- What and Why of Sorting 03:55 162 S10 - L02 -- Types of Sorting Techniques 07:15 163 S10 - L03 -- Sorting Terminologies 05:02 164 07:47 165 S10 - L05 -- Selection Sort 06:08 166 S10 - L06 -- Insertion Sort 08:52 167 08:35 168 11:12 169 S10 - L09 -- Quick Sort Part#1 12:37 170 S10 - L09 -- Quick Sort Part#2 06:01 171 12:42 172 S10 - L11 -- Sorting Techniques compared 02:15 173 S11 - L01 -- What and Why of Graphs 08:57 174 S11 - L02 -- Graph Terminologies 05:12 175 S11 - L03 -- Types of Graphs 04:00 176 S11 - L04 -- Graph Representation in Code 07:09 177 S11 - L05 -- BFS Algorithm 08:30 178 S11 - L06 -- BFS Time Complexity 06:34 179 S11 - L07 -- DFS Algorithm 08:08 180 S11 - L08 -- DFS Time Complexity 05:59 181 04:27 182 S11 - L10 -- What is Topological Sort 03:45 183 S11 - L11 -- Topological Sort Dry Run 06:33 184 S11 - L12 -- Why Topological Sort Works 07:12 185 S11 - L13 -- Topological Sort Algorithm 06:39 186 S11 - L14 -- What is Single Source Shortest Path Problem(SSSP) 06:30 187 S11 - L15 -- BFS for SSSP 08:08 188 S11 - L16 -- Why BFS does not works for Weighted Graph SSSP 04:04 189 S11 - L17 -- Why DFS does not works for SSSP 03:02 190 S11 - L18 -- Dijkstra for SSSP 11:17 191 S11 - L19 -- Why Dijkstra does not work for Negative Cycle 06:07 192 S11 - L20 -- BellmanFord Dry run for SSSP 09:48 193 S11 - L21 -- BellanFord Algorithm for SSSP 04:28 194 S11 - L22 -- How Bellman Ford works for Negative Cycle 09:09 195 S11 - L23 -- Why BellmanFord runs for V-1 times 10:09 196 S11 - L24 -- BFS vs Dijkstra vs BellmanFord 04:33 197 S11 - L25 -- What is All Pair Shortest Path Problem(APSP) 05:35 198 S11 - L26 -- Dry run of BFS Dijkstra Bellman for APSP 05:18 199 S11 - L27 -- Floyd Warshall Algorithm for APSP 10:09 200 S11 - L28 -- Why Floyd Warshall Algorithm always works 08:13 201 S11 - L29 -- Why Floyd does not works for Negative Cycle 03:50 202 S11 - L30 -- BFS vs Dijkstra vs Bellman vs Floys 04:25 203 S11 - L31 -- What is Minimum Spanning Tree (MST) 04:39 204 S11 - L32.1 -- DisjointSet 08:49 205 S11 - L32.2 -- Kruskals Algorithm 12:40 206 S11 - L33 -- Prims Algorithm Dry Run 06:34 207 S11 - L34 -- Prims Algorithm Explained 05:23 208 S11 - L35 -- Prims vs Kruskal 02:34 209 S12.1 - L01 -- Magic Framework 04:46 210 S12.2 - L01 -- Greedy Algo Introduction 06:18 211 S12.2 - L02 -- Known Algos 10:51 212 S12.2 - L03 -- Activity Selection Problem 08:05 213 S12.2 - L04 -- Coin Change Problem 09:07 214 S12.2 - L05 -- Fractional Knapsack Problem 11:56 215 S12.3 - L01 -- What and Why of Divide&Conquer 07:35 216 S12.3 - L02 -- Binary Search, Quick, Merge Sortt 05:48 217 S12.3 - L03 -- Fibonacci Series 03:32 218 S12.3 - L04 -- Number Factor 09:38 219 S12.3 - L05 -- House thief 08:49 220 S12.3 - L06 -- Convert One String to Another 12:58 221 S12.3 - L07 -- Zero-One Knapsack 07:49 222 S12.3 - L08 -- Longest Common Subsequence 08:52 223 S12.3 - L09 -- Longest Palindromic Subsequence 09:47 224 S12.3 - L10 -- Longest Palindromic Substring 09:11 225 S12.3 - L11 -- Min Cost to Reach End of Array 07:13 226 S12.3 - L12 -- Number of Paths to reach last cell with given Cost 10:30 227 S12.4 - L01 -- What and Why of Dynamic Programming 04:46 228 S12.4 - L02 -- Top Down Approach 06:41 229 S12.4 - L03 -- Bottom Up Approach 07:45 230 S12.4 - L04 -- Is Merge Sort Dynamic Programming ? 03:57 231 S12.4 - L05 -- Number Factor Problem 15:26 232 S12.4 - L06 -- HouseThief Problem 12:15 233 S12.4 - L07 -- Convert One String to Another 11:20 234 S12.4 - L08 -- Zero One Knapsack Problem 13:16 235 S12.4 - L09 -- Longest Common Subsequence 10:20 236 S12.4 - L10 -- Longest Palindromic Subsequence 10:53 237 S12.4 - L11 -- Longest Palindromic Substring 12:34 238 S12.4 - L12 -- Min Cost to Reach End of Array 12:35 239 S12.4 - L13 -- Ways to Reach last cell 24:53 