C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 5)

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 5)

   Friday, July 17, 2026   

Starting a new Lecture Notes Series on C++ Full Course | C++ Tutorial | Data Structures & Algorithms

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Lecture 199: Optimal Game Strategy - Dynamic Programming | C++ Placement Course | Lecture 35.12

Lecture 200: Number of Subsequences - Dynamic Programming | C++ Placement Course | Lecture 35.13

Lecture 201: Count Number of Binary Strings - Dynamic Programming | C++ Placement Course | Lecture 35.14

Lecture 202: 0-N Knapsack - Dynamic Programming | C++ Placement Course | Lecture 35.15

Lecture 203: Kadane Algorithm - Dynamic Programming | C++ Placement Course | Lecture 35.5

Lecture 204: Maximum Length of Bitonic Subsequence - Dynamic Programming | C++ Placement Course | Lecture 35.19

Lecture 205: Friends Paring Problem - Dynamic Programming | C++ Placement Course | Lecture 35.20

Lecture 206: Ugly Numbers - Dynamic Programming | C++ Placement Course | Lecture 35.18

Lecture 207: LCS with 3 Strings - Dynamic Programming | C++ Placement Course | Lecture 35.16

Lecture 208: K-Ordered LCS - Dynamic Programming | C++ Placement Course | Lecture 35.17

Lecture 209: Tries - Introduction | C++ Placement Course | Lecture 36.1

Lecture 210: XOR SubArray - Tries Challenges | C++ Placement Course | Lecture36.2

Lecture 211: Trie bash - Challenge | C++ Placement Course | Lecture 36.3

Lecture 212: Digital Dictionary - Tries Challenges | C++ Placement Course | Lecture 36.4

Lecture 213: Extended Euclid Algorithm - Number Theory Advanced | C++ Placement Course | Lecture 37.1

Lecture 214: Multiplicative Modulo Inverse - Number Theory Advanced | Lecture 37.2

Lecture 215: Euler Totient Function - Number Theory Advanced | C++ Placement Course | Lecture 37.3

Lecture 216: Binary Exponentiation - Number Theory Advanced | C++ Placement Course | Lecture 37.4

Lecture 217: Fermat Little and Wilson Theorem - Number Theory Advanced | C++ Placement Course | Lecture 37.5

Lecture 218: Boring Factorials SPOJ - Number Theory Advanced | C++ Placement Course | Lecture 37.6

Lecture 219: Introduction, Fibonacci in Log(n) - Matrix Exponentiation | C++ Placement Course | Lecture 38.1

Lecture 220: String Hashing - String Algorithms | C++ Placement Course | Lecture 39.1

Lecture 221: SubStr() Function - String Algorithm | C++ Placement Course | Lecture 39.2

Lecture 222: KMP Algorithms - String Algorithm | C++ Placement Course | Lecture 39.3

Lecture 223: Rabin Karp - String Algorithms | C++ Placement Course | Lecture 39.4

Lecture 224: Guide to Interactive Problems | C++ Placement Course | Lecture 43

Lecture 225: Segment Tree - Introduction and Build | C++ Placement Course | Lecture 40.1

Lecture 226: Query in Segment Tree | C++ Placement Course | Lecture 40.2

Lecture 227: Maximum and Minimum Queries/Update | C++ Placement Course | Lecture 40.4

Lecture 228: Number of minimums on a segment | C++ Placement Course | Lecture 40.5

Lecture 229: User Snippets in VSCode | C++ Placement Course | Lecture 40.6

Lecture 230: Segment with Max Sum | C++ Placement Course | Lecture 40.7

Lecture 231: Kth One - Segment Tree | C++ Placement Course | Lecture 40.8

Lecture 232: First Element at Least X - Segment Tree | C++ Placement Course | Lecture 40.9

Lecture 233: Nested Segments - Segment Tree | C++ Placement Course | Lecture 40.12

Lecture 234: Intersecting Segments - Segment Tree | C++ Placement Course | Lecture 40.13

Lecture 235: Fenwick Tree - Introduction | C++ Placement Course | Lecture 41.1

Lecture 236: Point & Range Updates - Fenwick Tree | C++ Placement Course | Lecture 41.2

Lecture 237: Count Inversion - Fenwick Tree | C++ Placement Course | Lecture 41.3

Lecture 238: Square Root Decomposition - Introduction | C++ Placement Course | Lecture 42.1

Lecture 239: RMQSQ - Spoj | C++ Placement Course | Lecture 42.2

Lecture 240: Mo's Algorithm - Square Root Decomposition | Lecture 42.3

Lecture 241: DQueary - SPOJ | C++ Placement Course | Lecture 42.4

Lecture 242: Policy Based Data Structures | C++ Placement Course | Lecture 44

Lecture 243: Book Allocation or Allocate Books Problem | DSA Series - Binary Search

Lecture 244: Painter's Partition Problem | DSA Placement Series - Binary Search | Lecture 22

Lecture 245: Aggressive Cows Problem | DSA Placement Series - Binary Search | Lecture 23

C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 4)

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 4)

   Thursday, July 16, 2026   

Starting a new Lecture Notes Series on C++ Full Course | C++ Tutorial | Data Structures & Algorithms

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Lecture 151: Heap STL | C++ Placement Course | Lecture 31.3

Lecture 152: Heaps - Median of Running Stream | C++ Placement Course | Lecture 31.4

Lecture 153: Heaps - Merge K sorted Arrays | C++ Placement Course

Lecture 154: Heap -Smallest Sequence with sum K | C++ Placement Course | Lecture 31.6

Lecture 155: Hashing - Introduction to Hasing | C++ Placement Coure | Lecture 32.1

Lecture 156: Hashing STL - C++ Placement Course | Lecture 32.2

Lecture 157: Hashing - Count frequency of elements | C++ Placement Course | Lecture 32.3

Lecture 158: Hashing - Vertical Order Print | C++ Placement Course | Lecture 32.4

Lecture 159: Hashing - Number of Subarrays with Sum Zero | C++ Placement Course | Lec 32.5

Lecture 160: Hashing - Sliding Window Technique | C++ Placement Course

Lecture 161: Hashing - TOP K MOST FREQUENT ELEMENTS | C++ Placement Course | Lecture 32.7

Lecture 162: Sudoku Solver - Hashing | C++ Placement Course | Lecture 32.8

Lecture 163: Greedy Algorithm - Introduction | C++ Placement Course Lecture 33.1

Lecture 164: Indian Coin Change - Greedy Algorithm | C++ Placement Course | Lecture 33.2

Lecture 165: Activity Selection Problem - Greedy Algorithm | C++ Placement Course | Lecture 33.3

Lecture 166: Fractional Knapsack - Greedy Algorithm | C++ Placement Course | Lecture 33.4

Lecture 167: Optimal Pattern Merge - Greedy Algorithm | C++ Placement Course | Lecture 33.5

Lecture 168: Expedi - Greedy Algorithm | C++ Placement Course | Lecture 33.6

Lecture 169: Expedi - Greedy Algorithm | C++ Placement Course | Lecture 33.6

Lecture 170: Graphs - Introduction | C++ Placement Course | Lecture 34.1

Lecture 171: Dynamic Programming - Introduction | C++ Placement Course | Lecture 35.1

Lecture 172: Graph Terminologies | C++ Placement Course | Lecture 34.2

Lecture 173: Graphs - Representation | C++ Placement Course | Lecture 34.3

Lecture 174: BFS - Breadth First Search | C++ Placement Course | Lecture 34.4

Lecture 175: DFS - Depth First Search | C++ Placement Course | Lecture 34.5

Lecture 176: Graphs - Topological Sort | C++ Placement Course | Lecture 34.6

Lecture 177: Cycle Detection in Undirected Graphs | C++ Placement Course | Lecture 34.7

Lecture 178: Cycle Detection in Directed Graph | C++ Placement Course | Lecture 34.8

Lecture 179: Connected Components | C++ Placement Course | Lecture 34.9

Lecture 180: Bipartite Graph - C++ Placement Course | Lecture 34.10

Lecture 181: Disjoint Set Union - Graphs | C++ Placement Course | Lecture 34.11

Lecture 182: Cycle Detection in Undirected Graph using DSU | C++ Placement Course | Lecture 34.12

Lecture 183: Cycle Detection in Undirected Graph using DSU | C++ Placement Course | Lecture 34.12

Lecture 184: Kruskal's Algorithm | C++ Placement Course | Lecture 34.13

Lecture 185: Kruskal's Algorithm | C++ Placement Course | Lecture 34.13

Lecture 186: Dijkstra's Algorithm | C++ Placement Course | Lecture 34.15

Lecture 187: Bellman Ford Algorithm | C++ Placement Course | Lecture 34.16

Lecture 188: Floyd Warshall Algorithm | C++ Placement Course | Lecture 34.17

Lecture 189: Snakes and Ladders - Graphs | C++ Placement Course | Lecture 34.18

Lecture 190: Graphs - Surrounded Region | C++ Placement Course | Lecture 34.19

Lecture 191: Fibonacci Sequence - Dynamic Programming | C++ Placement Course | Lecture 35.2

Lecture 192: Minimum Number of Squares - Dynamic Programming | C++ Placement Course | Lecture 35.3

Lecture 193: Coin Change Problem - Dynamic Programming | C++ Placement Course | Lecture 35.4

Lecture 194: 01 Knapsack - Dynamic Programming | C++ Placement Course | Lecture 35.7

Lecture 195: Longest Increasing Subsequence - Dynamic Programming | C++ Placement Course | Lecture 35.8

Lecture 196: Longest Common Subsequence - Dynamic Programming | C++ Placement Course | Lecture 35.9

Lecture 197: Matrix Chain Multiplication - Dynamic Programming | C++ Placement Course | Lecture 35.10

Lecture 198: Minimum Jumps to Reach End - Dynamic Programming | C++ Placement Course | Lecture 35.11

C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 3)

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 3)

   Thursday, July 16, 2026   

Starting a new Lecture Notes Series on C++ Full Course | C++ Tutorial | Data Structures & Algorithms

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Lecture 103: Stacking using Queues (Method 2) | C++ Placement Course | Lecture 24.4.2

Lecture 104: Sliding Window Maximum using Deque | C++ Placement Course | Lecture 25.1

Lecture 105: Largest Rectangle Code | C++ Placement Course | Lecture 25.2

Lecture 106: Trapping Rainwater | C++ Placement Course | Lecture 25.3

Lecture 107: Redundant Parenthesis | C++ Placement Course | Lecture 25.4

Lecture 108: The Stock Span Problem | C++ Placement Course | Lecture 25.5

Lecture 109: Two Pointers | Three Sum Problem | C++ Placement Course | Lecture 26.1

Lecture 110: Max Consecutive Ones | C++ Placement Course | Lecture 26.2

Lecture 111: Longest substring without repeating characters | C++ Placement Course | Lecture 26.3

Lecture 112: Binary Tree Introduction | C++ Placement Course | Lecture 27.1

Lecture 113: Binary Tree Traversals| Preorder, Inorder, Postorder Traversal | C++ Placement Course | Lecture 27.2

Lecture 114: Build Tree from Preorder and Inorder | C++ Placement Course | Lecture 27.3

Lecture 115: Build Tree Postorder and Inorder | C++ Placement Course | Lecture 27.4

Lecture 116: Level Order Traversal , Sum at Kth Level In Binary Tree | C++ Placement Course | Lecture 27.5

Lecture 117: Count and Sum of Nodes | C++ Placement Course | Lecture 27.6

Lecture 118: Height and Diameter in Binary Tree | C++ Placement Course | Lecture 27.7

Lecture 119: Sum Replacement in Binary Tree | C++ Placement Course | Lecture 27.8

Lecture 120: Height Balanced Binary Tree | C++ Placement Course | Lecture 27.9

Lecture 121: Right View of Binary Tree | C++ Placement Course | Lecture 27.10

Lecture 122: Left View of Binary Trees | C++ Placement Course | Lecture 27.11

Lecture 123: Shortest Distance between 2 Nodes | C++ Placement Course | Lecture 27.12

Lecture 124: Flatten a Binary Tree | C++ Placement Course | Lecture 27.13

Lecture 125: Nodes at Distance K in Binary Tree | C++ Placement Course | Lecture 27.14

Lecture 126: Lowest Common Ancestor in Binary Tree | C++ Placement Course | Lecture 27.15

Lecture 127: Max Sum Path from One Node to Another in Binary Tree | C++ Placement Course | Lecture 27.16

Lecture 128: Binary Search Trees | Introduction & Build | C++ Placement Course | Lecture 28.1

Lecture 129: Search and Delete in Binary Search Tree | C++ Placement Course | Lecture 28.2

Lecture 130: Construct Binary Search Tree from Preorder | C++ Placement Course | Lecture 28.3

Lecture 131: Check for Binary Search Tree | C++ Placement Course | Lecture 28.4

Lecture 132: Build Balanced BST from Sorted Array | C++ Placement Course | Lecture 28.5

Lecture 133: Catalan Numbers Application | C++ Placement Course | Lecture 28.6

Lecture 134: Zig Zag Traversal Binary Search Tree | C++ Placement Course | Lecture 28.7

Lecture 135: Identical Binary Search Tree | C++ Placement Course | Lecture 28.8

Lecture 136: Largest Binary Search Tree in BT | C++ Placement Course | Lecture 28.10

Lecture 137: Recover Binary Search Tree | C++ Placement Course | Lecture 28.11

Lecture 138: Set & Multiset | Standard Template Library | C++ Placement Course | Lecture 28.12

Lecture 139: Place Elements to Maximise Minimum Distance | C++ Placement Course | Lecture 29.1

Lecture 140: Page Allocation Problem | C++ Placement Course | Lecture 29.2

Lecture 141: Painters Partition Problem | C++ Placement Course | Lecture 29.3

Lecture 142: Search in Sorted & Rotated Array | C++ Placement Course | Lecture 29.4

Lecture 143: Find the Peak Element | C++ Placement Course | Lecture 29.5

Lecture 144: Max Sum Subarray | Sliding Window Challenge | C++ Placement Course | Lecture 30.1

Lecture 145: Minimum Subarray Size | Sliding Window Challenge | C++ Placement Course | Lecture 30.2

Lecture 146: Form Number Divisible by 3 | Sliding Window Challenge | C++ Placement Course | Lecture 30.3

Lecture 147: Subarray with Palindromic Concatenation | C++ Placement Course | Lecture 30.4

Lecture 148: Perfect Numbers in Subarrays | C++ Placement Course | Lecture 30.5

Lecture 149: Heap Intro Final Export for Upload

Lecture 150: HeapsSort | C++ Placement Course | Lecture 31.2

C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 2)

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 2)

   Wednesday, July 15, 2026   

Starting a new Lecture Notes Series on C++ Full Course | C++ Tutorial | Data Structures & Algorithms

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Lecture 52: 13. Strings in C++ | Guaranteed Placement Course | Lecture 13

Lecture 53: 13.2 Strings Challenges | C++ Placement Course

Lecture 54: 14.1 BIT Manipulation in 11 minutes | C++ Placement Course

Lecture 55: 14.2 BIT Manipulation Challenges | C++ Placement Course

Lecture 56: 14.3 BIT Manipulation | Challenges - Part 2 | Questions asked by Top MNC's

Lecture 57: 15.1 Sieve of Eratosthenes | Challenge | C++ Placement Course

Lecture 58: 15.2 Inclusion- Exclusion Principle | GCD | C++ Placement Course

Lecture 59: 16.1 Recursion - Introduction | C++ Placement Course

Lecture 60: 16.2 Recursion - Challenges | C++ Placement Course

Lecture 61: 7 Best Problems on Recursion | Recursion in C++ | Placement Course | Lec 16.3

Lecture 62: Advanced Recursion Problems | C++ Placement Course | Lecture 16.4

Lecture 63: Recursion | Last Lecture on Advanced Problems | Lecture 16.4

Lecture 64: Backtracking - Rat in a Maze | C++ Placement Course | Lecture 18.1

Lecture 65: Permutation - Return all possible permutations | C++ Placement Course | Lecture 17

Lecture 66: N-Queen Problem - Backtracking | C++ Placement Course - 18.2

Lecture 67: Merge Sort | Code and Explanation | C++ Course - 19.1

Lecture 68: Quick Sort | Code and Explanation | C++ Course - 19.2

Lecture 69: Vectors and Pair | C++ Course - 19

Lecture 70: Count Sort | C++ Placement Course | Lecture 20.1

Lecture 71: DNF Sort | C++ Placement Course | Lecture 20.2

Lecture 72: Wave Sort | C++ Placement Course - 20.3

Lecture 73: Count Inversion - Merge Sort | C++ Placement Course - 19.3

Lecture 74: Object Oriented Programming in C++ | Important Concept | Lecture 21.1

Lecture 75: Inheritance in OOP's | C++ Placement Course | Lecture 21.3

Lecture 76: Polymorphism in Object Oriented Programming | C++ Placement Course Lecture 21.4

Lecture 77: Introduction to Linked List | C++ Placement Course | Lecture 22

Lecture 78: Deletion in Linked List | C++ Placement Course | Lecture 22.2

Lecture 79: Reverse a Linked List | C++ Placement Course | Lecture 22.3

Lecture 80: Reverse K Nodes in a Linked List | C++ Placement Course | Lecture 22.4

Lecture 81: Reverse K Nodes in a Linked List | C++ Placement Course | Lecture 22.4

Lecture 82: Doubly Linked List | Data Structures & Algorithms | C++ Placement Course | Lecture 22.6

Lecture 83: Append Last K Nodes of a Linked List | C++ Placement Course | Lecture 22.7

Lecture 84: Find Intersection point of 2 Linked List | Lecture 22.8

Lecture 85: Merge 2 Sorted Linked List | C++ Placement Course | Lecture 22.9

Lecture 86: Circular Linked List - C++ Placement Course | Lecture 22.10

Lecture 87: Put Even Position Nodes after Odd Position Nodes | C++ Placement Course | Lecture 22.11

Lecture 88: 2021 - Top 5 Programming Language for College Students 2021

Lecture 89: Time Complexity using Masters Theorem | C++ Placement Course | Lecture 16.5

Lecture 90: Stack Data Structure - Introduction | C++ Placement Course | Lecture 23.1

Lecture 91: Reverse a Sentence using Stacks | Stack Challenge | C++ Placement Course | Lecture 23.2

Lecture 92: Reverse a Stack | C++ Placement Course | Lecture 23.3

Lecture 93: Introduction to Prefix, Infix and Postfix | C++ Placement Course | Lecture 23.4

Lecture 94: Prefix Expression Evaluation | C++ Placement Course | Lecture 23.5

Lecture 95: Postfix Expression Evaluation | C++ Placement Course | Lecture 23.6

Lecture 96: Infix to Postfix - Stack Challenges | C++ Placement Course | Lecture 23.7

Lecture 97: Infix to Prefix | C++ Placement Course | Lecture 23.8

Lecture 98: Balanced Parenthesis | C++ Placement Course | Lecture 23.9

Lecture 99: Introduction to Queue Data Structure | C++ Placement Course | Lecture 24.1

Lecture 100: Linked List Implementation of Queues | C++ Placement Course | Lecture 24.2

Lecture 101: Queue using Stack | C++ Placement Course | Lecture 24.3

Lecture 102: Stack using Queue | C++ Placement Course | Lecture 24.4

C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 1)

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms (Hindi) (Part 1)

   Wednesday, July 15, 2026   

Starting a new Lecture Notes Series on C++ Full Course | C++ Tutorial | Data Structures & Algorithms

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C++ Full Course | C++ Tutorial | Data Structures & Algorithms By Lecture Notes together!

Lecture 1: 1. Introduction to C++ | Data Structures and Algorithms | College Placement Course | Lecture 1

Lecture 2: Lecture 1 : Flowchart & Pseudocode + Installation | DSA Series by Shradha Khapra Ma'am | C++

Lecture 3: Lecture 2 : Variable, Data Types & Operators | DSA Series by Shradha Ma'am | C++

Lecture 4: Lecture 3: Conditional Statements & Loops | DSA Series by Shradha Ma'am | C++

Lecture 5: 25 - Lecture 4: Patterns | DSA Series by Shradha Khapra Ma'am | C++

Lecture 6: Lecture 5: Functions | DSA Series by Shradha Khapra Ma'am | C++

Lecture 7: Binary Number System | DSA Series by Shradha Khapra Ma'am | C++

Lecture 8: Bitwise Operators, Data Type Modifiers & more | DSA Series by Shradha Khapra Ma'am | C++

Lecture 9: Array Data Structure - Part1 | DSA Series by Shradha Khapra Ma'am | C++

Lecture 10: Vectors in C++ | Arrays Part 2 | DSA Series by Shradha Ma'am | Lecture 9

Lecture 11: Kadane's Algorithm | Maximum Subarray Sum | DSA Series by Shradha Ma'am

Lecture 12: Majority Element | Brute- Better-Best Approach | Moore's Voting Algorithm | & Pair Sum

Lecture 13: Time & Space Complexity - DSA Series by Shradha Ma'am

Lecture 14: Buy and Sell Stock Problem and Pow(X,N) Power exponential Problem - Leetcode | DSA Series

Lecture 15: Container with Most Water Problem | Brute & Optimal Solution | Two Pointer Approach - Leetcode 11

Lecture 16: Product of Array Except Self | Brute to Optimal Solution | Leetcode 238

Lecture 17: Pointers in C++ | In Detail | DSA Series by Shradha Ma'am

Lecture 18: Binary Search Algorithm - Iterative and Recursive Method | [Theory + Code] with Example

Lecture 19: Search in Rotated Sorted Array | Binary Search | Leetcode 33

Lecture 20: Peak Index in Mountain Array | Binary Search | Leetcode 852

Lecture 21: Single Element in Sorted Array | Binary Search | DSA Series Lecture 20

Lecture 22: DSA Complete Series 🚀 : Data Structures & Algorithms | by Shradha Khapra Ma'am

Lecture 23: VS Code Installation for C++ in Windows | Step by step process explanation

Lecture 24: 2.1 Data Types & Type Modifiers | Data Structures & Algorithms Course in C++ | Lecture 2.1

Lecture 25: 2.2 Input/Output in C++ | Data Structures and Algorithm Course in C++ | Lecture 2.2

Lecture 26: 2.3 If/else statement in C++ programming | Data Structure and Algorithm Course | Lecture 2.3

Lecture 27: 2.4 Introduction to Loops in C++ programming | Guaranteed Placement Course | Lecture 2.4

Lecture 28: 3.1 Break and Continue statement in C++ Programming | Guaranteed Placement Course | Lecture 3.1

Lecture 29: 3.2 Switch-Case statement in C++ Programming | Guaranteed Placement Course | Lecture 3.2

Lecture 30: 3.3 Operators in C++ Programming | Guaranteed Placement Course | 3.3

Lecture 31: 4.1 Awesome Pattern Questions -1 | Guaranteed Placement Course

Lecture 32: 4.2 Advanced Pattern Questions in C++ | Guaranteed Placement Course | Lecture 4.2

Lecture 33: 5.1 Binary Number System | Guaranteed Placement Course | Lecture 5.1

Lecture 34: 5.2 How to reverse a number | Check if a number is Prime or Armstrong | C++ Placement Course | # 5.2

Lecture 35: 6.1 Functions in C++ | Guaranteed Placement Course

Lecture 36: 6.2 Functions Challenges | C++ Guaranteed Course | Lecture 6.2

Lecture 37: 6.3 Advanced Placement Questions on Functions | C++ Placement Course

Lecture 38: 7.1 Time Complexity | C++ Placement Course

Lecture 39: 8.1 Introduction to Arrays in C++ | Guaranteed Placement Course

Lecture 40: 8.2 Searching in Arrays | Linear and Binary Search | C++ Placement Course |

Lecture 41: 8.3.1 Sorting in Arrays | Selection Sort | C++ Placement Course

Lecture 42: 8.3.2 Bubble Sort | Sorting in C++ | Guaranteed Placement Course

Lecture 43: 8.3.3 Insertion Sort | Sorting Algorithms | C++ Placement Course |

Lecture 44: 8.4 Array Challenges | C++ Placement Course

Lecture 45: 8.5 Arrays - Q's asked by Top MNC's | C++ Placement Course

Lecture 46: 8.6 Subarrays - Challenges | Questions asked by Top MNC's | C++ Placement Course

Lecture 47: 9.1 Two Dimensional Arrays | 2D Arrays | C++ Placement Course

Lecture 48: 9.2 "2D Array" Challenges | Asked by Top MNC's | C++ Placement Course

Lecture 49: 10. Character Arrays | C++ Placement Course

Lecture 50: 11. Pointers in C++ | Guaranteed Placement Course

Lecture 51: 12. Stack & Heap | C++ Placement Course

100 Days of Deep Learning (Hindi) (Part 2)

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100 Days of Deep Learning (Hindi) (Part 2)

   Saturday, June 27, 2026   

Starting a new Lecture Notes Series on 100 Days of Deep Learning

Youtube Lecture Playlist Credits 

Channel Name: CampusX

So Let Us Start to This Journey of Learning 

100 Days of Deep Learning By Lecture Notes together!

Lecture 43: Padding & Strides in CNN | CNN Lecture 4 | Deep Learning

Lecture 44: Pooling Layer in CNN | MaxPooling in Convolutional Neural Network

Lecture 45: CNN Architecture | LeNet -5 Architecture

Lecture 46: Comparing CNN Vs ANN | CampusX

Lecture 47: Backpropagation in CNN | Part 1 | Deep Learning

Lecture 48: CNN Backpropagation Part 2 | How Backpropagation works on Convolution, Maxpooling and Flatten Layers

Lecture 49: Cat Vs Dog Image Classification Project | Deep Learning Project | CNN Project

Lecture 50: Data Augmentation in Deep Learning | CNN

Lecture 51: Pretrained models in CNN | ImageNET Dataset | ILSVRC | Keras Code

Lecture 52: What does a CNN see? | Visualizing CNN Filters and Feature Maps | CampusX

Lecture 53: What is Transfer Learning? Transfer Learning in Keras | Fine Tuning Vs Feature Extraction

Lecture 54: Keras Functional Model | How to build non-linear Neural Networks?

Lecture 55: Why RNNs are needed | RNNs Vs ANNs | RNN Part 1

Lecture 56: Recurrent Neural Network | Forward Propagation | Architecture

Lecture 57: RNN Sentiment Analysis | RNN Code Example in Keras | CampusX

Lecture 58: Types of RNN | Many to Many | One to Many | Many to One RNNs

Lecture 59: How Backpropagation works in RNN | Backpropagation Through Time

Lecture 60: Problems with RNN | 100 Days of Deep Learning

Lecture 61: LSTM | Long Short Term Memory | Part 1 | The What? | CampusX

Lecture 62: LSTM Architecture | Part 2 | The How? | CampusX

Lecture 63: LSTM | Part 3 | Next Word Predictor Using | CampusX

Lecture 64: Gated Recurrent Unit | Deep Learning | GRU | CampusX

Lecture 65: Deep RNNs | Stacked RNNs | Stacked LSTMs | Stacked GRUs | CampusX

Lecture 66: Bidirectional RNN | BiLSTM | Bidirectional LSTM | Bidirectional GRU

Lecture 67: The Epic History of Large Language Models (LLMs) | From LSTMs to ChatGPT | CampusX

Lecture 68: Encoder Decoder | Sequence-to-Sequence Architecture | Deep Learning | CampusX

Lecture 69: Attention Mechanism in 1 video | Seq2Seq Networks | Encoder Decoder Architecture

Lecture 70: Bahdanau Attention Vs Luong Attention

Lecture 71: Introduction to Transformers | Transformers Part 1

Lecture 72: What is Self Attention | Transformers Part 2 | CampusX

Lecture 73: Self Attention in Transformers | Deep Learning | Simple Explanation with Code!

Lecture 74: Scaled Dot Product Attention | Why do we scale Self Attention?

Lecture 75: Self Attention Geometric Intuition | How to Visualize Self Attention | CampusX

Lecture 76: Why is Self Attention called "Self"? | Self Attention Vs Luong Attention in Depth Lecture | CampusX

Lecture 77: What is Multi-head Attention in Transformers | Multi-head Attention v Self Attention | Deep Learning

Lecture 78: Positional Encoding in Transformers | Deep Learning | CampusX

Lecture 79: Layer Normalization in Transformers | Layer Norm Vs Batch Norm

Lecture 80: Transformer Architecture | Part 1 Encoder Architecture | CampusX

Lecture 81: Masked Self Attention | Masked Multi-head Attention in Transformer | Transformer Decoder

Lecture 82: Cross Attention in Transformers | 100 Days Of Deep Learning | CampusX

Lecture 83: Transformer Decoder Architecture | Deep Learning | CampusX

Lecture 84: Transformer Inference | How Inference is done in Transformer? | Deep Learning | CampusX

100 Days of Deep Learning (Hindi) (Part 1)

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100 Days of Deep Learning (Hindi) (Part 1)

   Friday, June 26, 2026   

Starting a new Lecture Notes Series on 100 Days of Deep Learning

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Channel Name: CampusX

So Let Us Start to This Journey of Learning 

100 Days of Deep Learning By Lecture Notes together!

Lecture 1: 100 Days of Deep Learning | Course Announcement

Lecture 2: What is Deep Learning? Deep Learning Vs Machine Learning | Complete Deep Learning Course

Lecture 3: Types of Neural Networks | History of Deep Learning | Applications of Deep Learning

Lecture 4: What is a Perceptron? Perceptron Vs Neuron | Perceptron Geometric Intuition

Lecture 5: Perceptron Trick | How to train a Perceptron | Perceptron Part 2 | Deep Learning Full Course

Lecture 6: Perceptron Loss Function | Hinge Loss | Binary Cross Entropy | Sigmoid Function

Lecture 7: Problem with Perceptron

Lecture 8: MLP Notation

Lecture 9: Multi Layer Perceptron | MLP Intuition

Lecture 10: Forward Propagation | How a neural network predicts output?

Lecture 11: Customer Churn Prediction using ANN | Keras and Tensorflow | Deep Learning Classification

Lecture 12: Handwritten Digit Classification using ANN | MNIST Dataset

Lecture 13: Graduate Admission Prediction using ANN

Lecture 14: Loss Functions in Deep Learning | Deep Learning | CampusX

Lecture 15: Loss Functions in Deep Learning | Deep Learning | CampusX

Lecture 16: Backpropagation Part 2 | The How | Complete Deep Learning Playlist

Lecture 17: Backpropagation Part 3 | The Why | Complete Deep Learning Playlist

Lecture 18: Vanishing Gradient Problem in ANN | Exploding Gradient Problem | Code Example

Lecture 19: MLP Memoization | Complete Deep Learning Playlist

Lecture 20: Gradient Descent in Neural Networks | Batch vs Stochastics vs Mini Batch Gradient Descent

Lecture 21: How to Improve the Performance of a Neural Network

Lecture 22: Early Stopping In Neural Networks | End to End Deep Learning Course

Lecture 23: Data Scaling in Neural Network | Feature Scaling in ANN | End to End Deep Learning Course

Lecture 24: Dropout Layer in Deep Learning | Dropouts in ANN | End to End Deep Learning

Lecture 25: Dropout Layers in ANN | Code Example | Regression | Classification

Lecture 26: Regularization in Deep Learning | L2 Regularization in ANN | L1 Regularization | Weight Decay in ANN

Lecture 27: Activation Functions in Deep Learning | Sigmoid, Tanh and Relu Activation Function

Lecture 28: Relu Variants Explained | Leaky Relu | Parametric Relu | Elu | Selu | Activation Functions Part 2

Lecture 29: Weight Initialization Techniques | What not to do? | Deep Learning

Lecture 30: Xavier/Glorat And He Weight Initialization in Deep Learning

Lecture 31: Batch Normalization in Deep Learning | Batch Learning in Keras

Lecture 32: Optimizers in Deep Learning | Part 1 | Complete Deep Learning Course

Lecture 33: Exponentially Weighted Moving Average or Exponential Weighted Average | Deep Learning

Lecture 34: SGD with Momentum Explained in Detail with Animations | Optimizers in Deep Learning Part 2

Lecture 35: Nesterov Accelerated Gradient (NAG) Explained in Detail | Animations | Optimizers in Deep Learning

Lecture 36: AdaGrad Explained in Detail with Animations | Optimizers in Deep Learning Part 4

Lecture 37: RMSProp Explained in Detail with Animations | Optimizers in Deep Learning Part 5

Lecture 38: Adam Optimizer Explained in Detail with Animations | Optimizers in Deep Learning Part 5

Lecture 39: Keras Tuner | Hyperparameter Tuning a Neural Network

Lecture 40: What is Convolutional Neural Network (CNN) | CNN Intution

Lecture 41: CNN Vs Visual Cortex | The Famous Cat Experiment | History of CNN

Lecture 42: CNN Part 3 | Convolution Operation

Artificial Intelligence (Hindi)

CSE/IT SERIES

Artificial Intelligence (Hindi)

   Saturday, May 23, 2026   

Starting a new Lecture Notes Series on Artificial Intelligence

Youtube Lecture Playlist Credits 

Channel Name: Gate Smashers

So Let Us Start to This Journey of Learning 

Artificial Intelligence By Lecture Notes together!

Lecture 1: Lec-1: Artificial Intelligence Syllabus Discussion and Analysis for NTA UGC NET

Lecture 2: Lec-2: What's the FUTURE of Artificial Intelligence in 2025

Lecture 3: Lec-3: What is Artificial Intelligence | Learn AI with Real Life Examples | Can Machine Think??

Lecture 4: Lec-4: What is State Space Search | Introduction to Problem Solving in Artificial Intelligence

Lecture 5: Lec-5: Uninformed Vs Informed Search in Artificial Intelligence with Example

Lecture 6: Lec-6: Informed vs Uninformed vs Adversarial Search With Examples | Artificial Intelligence

Lecture 7: Lec-7: Breadth First Search (BFS) with example | Uninformed Search | Artificial Intelligence

Lecture 8: Lec-8: Depth First Search (DFS) with example | Uninformed Search | Artificial Intelligence

Lecture 9: Lec-9: Time & Space Complexity of BFS and DFS | Artificial Intelligence

Lecture 10: Lec-10: Bidirectional Search Algorithm in Artificial Intelligence in Hindi with Real Life Examples

Lecture 11: Lec-11: Best First Search Algorithm | How it Works | All Imp Points(Pros & Cons)

Lecture 12: Lec-12: Depth-Limited Search (DLS) Explained | Uninformed Search in AI

Lecture 13: Lec-13: Iterative Deepening Depth-First Search (IDDFS) | Artificial Intelligence

Lecture 14: Lec-14: 8-Puzzle Problem in Artificial Intelligence without Heuristic | All Imp Points | Must Watch

Lecture 15: Lec-15: What is Heuristic in AI | Why we use Heuristic | How to Calculate Heuristic | Must Watch

Lecture 16: Lec-16: How to Solve 8-Puzzle Problem with Heuristic(Informed Search) in Artificial Intelligence

Lecture 17: Lec-17: Generate and Test Search in Artificial Intelligence with Examples | Heuristic Search

Lecture 18: Lec-18: Beam Search Algorithm | All Imp Points | Heuristic Search Techniques

Lecture 19: Lec-19: Hill Climbing Algorithm in Artificial Intelligence with Real Life Examples| Heuristic Search

Lecture 20: Lec-20: A* algorithm in AI (artificial intelligence) in HINDI | A* algorithm with example

Lecture 21: Lec-21: How to Proof A* Admissible| Underestimation & Overestimation of A* in Hindi

Lecture 22: Lec-22: AO* algorithm in AI (artificial intelligence) in HINDI | AO* algorithm with example

Lecture 23: Lec-23: Introduction to Game Playing | Learn Game Playing Algorithms with Example

Lecture 24: Lec-24: Minimax Algorithm in Game Playing | Artificial Intelligence

Lecture 25: Lec-25: Alpha Beta Pruning in Hindi with Example | Artificial Intelligence

Lecture 26: Lec-26: Knowledge Representation and Reasoning | Logic, Semantic Net, Frames etc.

Lecture 27: Lec-27: Propositional Logic in Artificial Intelligence | Knowledge Representation | All Imp Points

Lecture 28: Lec-28: Introduction to Intelligent Agents and their types with Example in Artificial Intelligence

Lecture 29: Lec-29: Simple Reflex Agent in Artificial Intelligence with Example | Artificial Intelligence

Lecture 30: Lec-30: Model Based Reflex Agent in Artificial Intelligence in HINDI with Real Life Examples

Lecture 31: Lec-31: Goal Based Agents in Artificial Intelligence with real life examples in HINDI

Lecture 32: Lec-32: Utility Based Agents in Artificial Intelligence in Hindi with real life examples

Lecture 33: Lec-33: Fuzzy Logic in Artificial Intelligence with Example | Artificial Intelligence

Lecture 34: Lec-34: Various Operations in Fuzzy Logic with Example | Union, Intersection, Complement etc.

Lecture 35: Lec-35: Introduction to Neural Networks with Example in HINDI | Artificial Intelligence

Lecture 36: Lec-36: Natural Language Processing in Artificial Intelligence in Hindi | NLP with Demo and Examples

Lecture 37: Lec-37: Supervised, Unsupervised and Reinforcement Learning in Artificial Intelligence in Hindi

Lecture 38: Lec-38: Genetic Algorithm in Artificial Intelligence | Simplest Explanation with real life examples

Lecture 39: Lec-39: What is Constraint Satisfaction | Constraint Satisfaction Problem (CSP) in AI with Example

Lecture 40: Lec-40: How Constraint Satisfaction Algorithm Works | Explained with Interesting Example | AI

Lecture 41: Lec-41: Branch & Bound Algorithm with Example | Easiest Explanation of B&B with example

Lecture 42: Lec-42 : 0/1 Knapsack using Branch and Bound with example

Lecture 43: When There is Uncertainty

Lecture 44: Lec-43: Propositional Logic | Artificial Intelligence

Lecture 45: Lec-44: Predicate Logic | Artificial Intelligence

Lecture 46: Lec-45: How to write First order/Predicate logic | Artificial Intelligence

Lecture 47: Lec-46: Negation of Quantifiers | Predicate Logic | Logic with Certainty | Artificial Intelligence

Lecture 48: Lec-47: Questions on Propositional & Predicate logic | How to Solve Problems in Logic

Lecture 49: Lec-48: Bayes Theorem & Total Probability with Examples

Lecture 50: Lec-49 : Network with Examples | Easiest Explanation

Lecture 51: Lec-50: Question on Bayesian Network | Artificial Intelligence

Lecture 52: Lec-51: Bayesian Network Numerical Example #gate2025preparation

Lecture 53: Lec-52: Probabilistic Inference | Sampling | Artificial Intelligence

Lecture 54: Lec-53: Likelihood Weight Sampling | Inference through Sampling | Uncertainty in Artificial

Lecture 55: Lec-54: Question on Likelihood Sampling | Probabilistic Inference | Sampling | Artificial

Lecture 56: Lec-55: Rejection Sampling | Probabilistic Inference | Sampling | Artificial Intelligence

Lecture 57: Lec-56: Reasoning under Uncertainty in Artificial Intelligence

Lecture 58: Lec-57: Uncertainty probabilistic inference (Markov Model) | Artificial Intelligence

Lecture 59: Lec-58: Introduction to Hidden Markov Model | Artificial Intelligence

Lecture 60: Lec-31: Token & Parameters in LLama3 META Models | 8B & 70B Parameters Model | GPT model