Artificial Intelligence (Hindi)

   Saturday, May 23, 2026   

Starting a new Lecture Notes Series on Artificial Intelligence

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Channel Name: Gate Smashers

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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