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

Youtube Lecture Playlist Credits 

Channel Name: ScoreShala

So Let Us Start to This Journey of Learning 

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

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)

CSE/IT SERIES

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

Youtube Lecture Playlist Credits 

Channel Name: ScoreShala

So Let Us Start to This Journey of Learning 

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)

CONCEPTS SERIES

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)

CONCEPTS SERIES

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

   Friday, June 26, 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 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

Cloud Computing (Hindi)

CSE/IT SERIES

Cloud Computing (Hindi)

   Tuesday, May 05, 2026   

Starting a new Lecture Notes Series on Cloud Computing

Youtube Lecture Playlist Credits 

Channel Name: Gate Smashers

So Let Us Start to This Journey of Learning 

Cloud Computing By Lecture Notes together!

Lecture 1: Complete Cloud 🌧️ Computing Syllabus | Cloud Computing for Interviews, College & Universities Exam

Lecture 2: Lec-1: What is Cloud Computing | Evolution and Applications | Easiest introduction in Hindi

Lecture 3: Lec-2: Cloud Computing vs Others | Real life Example

Lecture 4: Lec-3: Introduction to Cloud 🌧️ Computing with Real Life Examples | Key Characteristics & Benefits

Lecture 5: Lec-4: Future of Cloud 🌧️ Computing | AI 🤖 as a Service | Artificial Intelligence as a Service

Lecture 6: Lec-5: Complete Roadmap 🛣️ Cloud 🌧️ Computing for Beginners | How to Master in Cloud Computing

Lecture 7: Lec-6: Career💰Options in Cloud 🌧️ Computing | Cloud Computing for Beginners

Lecture 8: Lec-7: Cloud🌧️ Architecture🗼with Real life examples | Cloud Computing Architecture

Lecture 9: Lec-8:Cloud Computing Services Models - Saas, Paas and Iaas explained in Hindi

Lecture 10: Lec-9: SaaS, PaaS & IaaS - Cloud Computing Made Simple!

Lecture 11: Lec-10: Various Standards & Frameworks in Cloud 🌧️ Computing

Lecture 12: Lec-11: Components of AWS Cloud 🌧️ | Cloud Computing🚀 Components

Lecture 13: Lec-12: Storage in Cloud 🌧️| Microsoft Azure Storage 🗃️Services with Real life examples

Lecture 14: Lec-13: OS Virtualization with Examples | Virtualization Types with Real life example

Lecture 15: Lec-14: Type 1 vs Type 2 Virtualization Explained: A Complete Guide for Cloud Computing Beginners

Lecture 16: Lec-15: What is Hypervisor | Types of Hypervisor

Lecture 17: Lec-16: Introduction to VMware & Hypervisor Ecosystem with Real life Applications | Cloud Computing

Lecture 18: Lec-17: Virtual Machine vs Containers 🫙| Cloud 🌧️ Computing

Lecture 19: Lec-18: Amazon AWS VPC & Microsoft Azure VNet | Cloud 🌧️ Network 🎛️ with Examples

Lecture 20: Lec-19: What is CIDR Addressing | Classless Inter-Domain Routing with Examples | Most Important

Lecture 21: Lec-20: Subnet in CIDR addressing with Easiest Example | Subnet in IP Addressing

Lecture 22: Lec-21: What are Ports in Networking 🛜 Why Ports are Used?

Lecture 23: Lec-22: SLA: Service Level Agreement in Cloud Computing | Need & Use of SLA

Lecture 24: Lec-23: Cost Models: Understanding CapEx vs. OpEx, consumption-based Pricing💰

Lecture 25: Lec-24: New Rules in Digital Personal Data Protection Act-2023

Lecture 26: Lec-25: Seven 7️⃣ Step Model of Cloud 🌧️ Migration | Cloud Computing for Beginners

Lecture 27: Lec-26: Challenge in Cloud Migration | Why it happens

Lecture 28: Lec-27: What is Multi Cloud 🌧️ with Examples | Cloud Computing for Beginners

Lecture 29: Lec-28: What is Serverless? | AWS Lambda vs EC2 | Serverless Vs Server Based

Lecture 30: Lec-29: What are MicroServices & its Uses | Microservice Architecture vs Monolithic with examples

Lecture 31: Lec-30: How to Create Instance on AWS EC2 | Amazon EC2 Explained with Live Demo

Lecture 32: Lec-31: What is Proxy Server🙋 & Reverse Proxy? Best Explanation with Real Life Examples

Lecture 33: Lec-32: What is Nginx? Best Explanation with Real Life Examples

Lecture 34: Lec-33: What is Version Control | with Real Life Example

Lecture 35: Lec-34: What is Docker 🚢 Best Explanation with Real Life Examples

Lecture 36: Lec-35: Best Docker Practice for Beginners | How Containers run in Docker with Implementation

Lecture 37: Lec-36: Image vs Container with Real Life Example & Demo

Lecture 38: Lec-37: What is Kubernetes☸️? Full Architecture🏗️with Real Life Examples

Lecture 39: Lec-38: How Development ➡️ Deployment is Done ✔️ | Pre Virtualization Era 🕰️

Lecture 40: Lec-39: Cloud Beginner Certification | Certified Cloud Practitioner | Best Way to make Career!

Lecture 41: Lec-40: OAuth 2.0 Explained Simply! 🔥 How Login with Google & Facebook Works?

Lecture 42: Lec-41: Cloud Security Threats and Mitigation Strategies

Lecture 43: Lec-42: What Are Endpoints? Master API & Cloud Security in Minutes!

Lecture 44: Lec-43: Introduction to Role-based access control (RBAC) | RBAC vs. ABAC

Software Engineering (English)

CSE/IT SERIES

Software Engineering (English)

   Saturday, May 02, 2026   

Starting a new Lecture Notes Series on Software Engineering

Youtube Lecture Playlist Credits 

Channel Name: Gate Smashers

So Let Us Start to This Journey of Learning 

Software Engineering By Lecture Notes together!

Lecture 1: Software Engineering Syllabus Discussion | Imp. for Competitive, College/University & Placements

Lecture 2: What is Software Engineering and its Evolution in Hindi with examples

Lecture 3: SDLC Life Cycle for Beginners | Software Development Life Cycle with Real life example

Lecture 4: Classic Waterfall model in Software Engineering

Lecture 5: Iterative Waterfall Model with example in Hindi

Lecture 6: V Shaped Model with examples | SDLC | Software Engineering

Lecture 7: Prototyping Model in Software Engineering

Lecture 8: Incremental Model in Software Engineering | SDLC

Lecture 9: Evolutionary Model with real life examples | Software Engineering

Lecture 10: Spiral Model in Software Engineering | SDLC

Lecture 11: Agile in Software Engineering

Lecture 12: SCRUM Model in Software Engineering | Agile Technology

Lecture 13: Comparison of All SDLC Models | Waterfall, Iterative, Prototype, Spiral, Increment, RAD, Agile etc.

Lecture 14: Software Requirements | Requirement Engineering | Feasibility Study, Elicitation, SRS, Validation

Lecture 15: Functional vs Non-functional Requirements | Requirement Engineering | Software Engineering

Lecture 16: Software Requirements Specification (SRS) | Software Engineering

Lecture 17: User Requirements with real life examples | User Requirement Specification | Software Engineering

Lecture 18: What is DFD? How to design DFD, Symbols, examples full explanation

Lecture 19: Levels of DFD | 0-Level, 1-Level, 2-Level with examples

Lecture 20: Logical vs Physical DFD with example | How Question asked from DFD?

Lecture 21: Function Oriented vs Object Oriented Design Approach | Software Design Approaches

Lecture 22: SPM(Software Project Management) with real life examples

Lecture 23: Risk Identification | Reactive vs Proactive Risk Management |Types of Risks with real life examples

Lecture 24: Risk Assessment with examples | Risk Management | Software Engineering

Lecture 25: Risk Control vs Risk Mitigation with example | Software engineering

Lecture 26: Basic COCOMO & Intermediate COCOMO with Numerical

Lecture 27: CPM (Critical Path Method) in Software Engineering | PERT/CPM Numerical

Lecture 28: Verification vs Validation in Software Engineering

Lecture 29: Types of Testing in Software Engineering | Levels of Testing

Lecture 30: Error Seeding in Software Testing | With Numerical Explanation

Lecture 31: 2 Imp. MCQs on Software Engineering | Must Watch|

Lecture 32: Question on Cyclomatic Complexity | Software Engg.

Lecture 33: Cohesion and Coupling in Software Engineering

Lecture 34: Unit Testing with examples in Software Engineering

Lecture 35: Integration Testing with examples | Software Engineering

Lecture 36: System Testing with examples | Software Engineering

Lecture 37: Types of System Testing | Software Engineering

Lecture 38: White box Testing with example | Software Engineering

Lecture 39: White Box vs Black Box Testing | Software Engineering

Lecture 40: Statement Coverage Technique | White Box Testing | Software Engineering

Lecture 41: Condition Coverage in White Box Testing | Software Engineering

Lecture 42: Data Flow Testing Technique in White Box Testing | Software Engineering

Lecture 43: Boundary Value Testing | Black 📦 Testing | Software Engineering with Real Life examples

Lecture 44: Perfective, Preventive, Adaptive, Corrective Maintenance in Software Engineering

Lecture 45: MTBF vs MTTR | Mean Time Between Failure | Mean Time to Repair

Lecture 46: Reverse◀️ Engineering👷with Real life examples🧐 | Software Engineering

Lecture 47: CASE Tools ⚒️ in Software Engineering👷

Lecture 48: Performance Testing with Real life examples | Software Engineering

Lecture 49: Regression Testing with Real Life Examples | Software Engineering

Lecture 50: Introduction to UML (Unified Modelling Language🤟) with examples | Software Engineering👷‍♂️👷‍♀️

Lecture 51: Use Case Diagram in UML | Software Engineering

Lecture 52: Sequence Diagram in UML | Software Engineering

Lecture 53: Activity Diagram in UML | Software Engineering

Lecture 54: Class Diagram in UML | Banking System (Real Life example) | Software Engineering

Lecture 55: Class Diagram in UML | OTT Platform (Real life example) | Easiest Explanation

Lecture 56: Object Diagram in UML | Class vs Object UML diagram with real life examples

Lecture 57: RAD Model

Lecture 58: RAD Model in Software Engineering | Rapid Application Development 🛠️ with Example

Lecture 59: Function Point(FP) vs Line of Code(LOC) | Project Size Estimation

Lecture 60: Function Point Analysis (FPA) | Function Point with Real life examples in Software Engineering

Lecture 61: Function Point Calculation | How Project Estimation is Done using FP | Numerical Explanation

Lecture 62: Aggregation vs Composition in UML with Examples | Software Engineering