technifyedWeekly list
Menu
Opportunities
Learn
Prepare
Get the weekly list

Gate Smashers

Artificial Intelligence (Complete Playlist)

via YouTube Video playlist

Compare with others

Overview

Master Artificial Intelligence (AI) | Complete AI Course from Basics to Advanced

🤖 Artificial Intelligence (AI) is revolutionizing industries like healthcare, finance, automation, and robotics. Whether you're a beginner, student, or preparing for competitive exams, certifications, or job interviews, this complete AI playlist covers everything you need to become an AI expert!

What You’ll Learn in This Playlist?

✅ Introduction to AI – What is AI, history, and real-world impact

✅ Types of AI – Narrow AI vs. General AI vs. Super AI

✅ Machine Learning & Deep Learning – How AI systems learn and evolve

✅ Search Algorithms in AI – BFS, DFS, A* algorithm explained

✅ Knowledge Representation & Reasoning – How AI understands and processes data

✅ Expert Systems & Fuzzy Logic – AI decision-making in uncertain conditions

✅ Natural Language Processing (NLP) – AI in chatbots, speech recognition & translation

✅ Computer Vision & Image Processing – AI-powered face and object recognition

✅ Robotics & AI Applications – Self-driving cars, automation, and smart assistants

✅ AI Ethics & Future Trends – Responsible AI, bias, and AI’s impact on jobs

✅ Career Opportunities in AI – Job roles, certifications, and roadmap

Who Is This Playlist For?

✔️ Engineering, BCA, MCA, and IT Students preparing for university exams

✔️ Beginners who want to start a career in Artificial Intelligence

✔️ Job seekers preparing for AI, Data Science, and Machine Learning interviews

✔️ IT Professionals & Developers looking to upskill in AI & Deep Learning

✔️ Entrepreneurs & Startups exploring AI-powered business solutions

🔥 Why Watch This Playlist?

🔹 50+ well-structured videos covering university syllabus & real-world applications

🔹 Hands-on demonstrations & coding examples using Python, TensorFlow, & PyTorch

🔹 Beginner-friendly yet industry-level depth

🔹 Explains top interview & AI certification topics in an easy-to-understand way

🔔 Subscribe now & start your journey in Artificial Intelligence! 🚀

#ArtificialIntelligence #AI #MachineLearning #DeepLearning #AIApplications #ComputerVision #NLP #SearchAlgorithms #AIinHealthcare #AIinFinance #AIinBusiness #DataScience #AIinAutomation #AIModelTraining #SupervisedLearning #UnsupervisedLearning #ReinforcementLearning #AIInterviewQuestions #AIResearch #NeuralNetworks #Robotics #AIEthics #AIJobs

Videos in this playlist 60

  1. Lec-1: Artificial Intelligence Syllabus Discussion and Analysis for NTA UGC NET
  2. Lec-2: What's the FUTURE of Artificial Intelligence in 2025
  3. Lec-3: What is Artificial Intelligence | Learn AI with Real Life Examples | Can Machine Think??
  4. Lec-4: What is State Space Search | Introduction to Problem Solving in Artificial Intelligence
  5. Lec-5: Uninformed Vs Informed Search in Artificial Intelligence with Example
  6. Lec-6: Informed vs Uninformed vs Adversarial Search With Examples | Artificial Intelligence
  7. Lec-7: Breadth First Search (BFS) with example | Uninformed Search | Artificial Intelligence
  8. Lec-8: Depth First Search (DFS) with example | Uninformed Search | Artificial Intelligence
  9. Lec-9: Time & Space Complexity of BFS and DFS | Artificial Intelligence
  10. Lec-10: Bidirectional Search Algorithm in Artificial Intelligence in Hindi with Real Life Examples
  11. Lec-11: Best First Search Algorithm | How it Works | All Imp Points(Pros & Cons)
  12. Lec-12: Depth-Limited Search (DLS) Explained | Uninformed Search in AI
  13. Lec-13: Iterative Deepening Depth-First Search (IDDFS) | Artificial Intelligence
  14. Lec-14: 8-Puzzle Problem in Artificial Intelligence without Heuristic | All Imp Points | Must Watch
  15. Lec-15: What is Heuristic in AI | Why we use Heuristic | How to Calculate Heuristic | Must Watch
  16. Lec-16: How to Solve 8-Puzzle Problem with Heuristic(Informed Search) in Artificial Intelligence
  17. Lec-17: Generate and Test Search in Artificial Intelligence with Examples | Heuristic Search
  18. Lec-18: Beam Search Algorithm | All Imp Points | Heuristic Search Techniques
  19. Lec-19: Hill Climbing Algorithm in Artificial Intelligence with Real Life Examples| Heuristic Search
  20. Lec-20: A* algorithm in AI (artificial intelligence) in HINDI | A* algorithm with example
  21. Lec-21: How to Proof A* Admissible| Underestimation & Overestimation of A* in Hindi
  22. Lec-22: AO* algorithm in AI (artificial intelligence) in HINDI | AO* algorithm with example
  23. Lec-23: Introduction to Game Playing | Learn Game Playing Algorithms with Example
  24. Lec-24: Minimax Algorithm in Game Playing | Artificial Intelligence
  25. Lec-25: Alpha Beta Pruning in Hindi with Example | Artificial Intelligence
  26. Lec-26: Knowledge Representation and Reasoning | Logic, Semantic Net, Frames etc.
  27. Lec-27: Propositional Logic in Artificial Intelligence | Knowledge Representation | All Imp Points
  28. Lec-28: Introduction to Intelligent Agents and their types with Example in Artificial Intelligence
  29. Lec-29: Simple Reflex Agent in Artificial Intelligence with Example | Artificial Intelligence
  30. Lec-30: Model Based Reflex Agent in Artificial Intelligence in HINDI with Real Life Examples
  31. Lec-31: Goal Based Agents in Artificial Intelligence with real life examples in HINDI
  32. Lec-32: Utility Based Agents in Artificial Intelligence in Hindi with real life examples
  33. Lec-33: Fuzzy Logic in Artificial Intelligence with Example | Artificial Intelligence
  34. Lec-34: Various Operations in Fuzzy Logic with Example | Union, Intersection, Complement etc.
  35. Lec-35: Introduction to Neural Networks with Example in HINDI | Artificial Intelligence
  36. Lec-36: Natural Language Processing in Artificial Intelligence in Hindi | NLP with Demo and Examples
  37. Lec-37: Supervised, Unsupervised and Reinforcement Learning in Artificial Intelligence in Hindi
  38. Lec-38: Genetic Algorithm in Artificial Intelligence | Simplest Explanation with real life examples
  39. Lec-39: What is Constraint Satisfaction | Constraint Satisfaction Problem (CSP) in AI with Example
  40. Lec-40: How Constraint Satisfaction Algorithm Works | Explained with Interesting Example | AI
  41. Lec-41: Branch & Bound Algorithm with Example | Easiest Explanation of B&B with example
  42. Lec-42 : 0/1 Knapsack using Branch and Bound with example
  43. When There is Uncertainty🤨#artificialintelligence #shorts #ytshorts #machinelearning
  44. Lec-43: Propositional Logic | Artificial Intelligence
  45. Lec-44: Predicate Logic | Artificial Intelligence
  46. Lec-45: How to write First order/Predicate logic | Artificial Intelligence
  47. Lec-46: Negation of Quantifiers | Predicate Logic | Logic with Certainty | Artificial Intelligence
  48. Lec-47: Questions on Propositional & Predicate logic | How to Solve Problems in Logic
  49. Lec-48: Bayes Theorem & Total Probability with Examples
  50. Lec-49 : Network with Examples | Easiest Explanation
  51. Lec-50: Question on Bayesian Network | Artificial Intelligence
  52. Lec-51: Bayesian Network Numerical Example #gate2025preparation
  53. Lec-52: Probabilistic Inference | Sampling | Artificial Intelligence
  54. Lec-53: Likelihood Weight Sampling | Inference through Sampling | Uncertainty in Artificial
  55. Lec-54: Question on Likelihood Sampling | Probabilistic Inference | Sampling | Artificial
  56. Lec-55: Rejection Sampling | Probabilistic Inference | Sampling | Artificial Intelligence
  57. Lec-56: Reasoning under Uncertainty in Artificial Intelligence
  58. Lec-57: Uncertainty probabilistic inference (Markov Model) | Artificial Intelligence
  59. Lec-58: Introduction to Hidden Markov Model | Artificial Intelligence
  60. Lec-31: Token & Parameters in LLama3 META Models | 8B & 70B Parameters Model | GPT model

Advantages and disadvantages

Advantages

  • Free and complete: every lecture is in the playlist, in order.
  • Watch at 1.5x, skip what you know, rewatch what you don't.
  • Taught in Hindi (or Hinglish), which many students find easier to follow.
  • Made for Indian students, with placement and exam context.
  • 2,860,110 views, so help and notes are easy to find.
  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (60 videos) you can see before you start.

Disadvantages

  • No certificate, deadlines or graded work.
  • Quality and depth vary: check that the playlist is finished before you start.
  • Less depth than a university course on some topics.
  • No certificate.
  • No graded assignments or feedback.
  • Recorded in 2019: tools may have changed since.

Some points apply to every course of this kind; see how we rank.

Free

  • Free: Watch on YouTube, no account needed.
  • Certificate: None. Code or take notes along to make it stick.

Gate Smashers is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (76/100). GATE and university CS subjects in Hindi.

Similar courses

Compare these

Massachusetts Institute of Technology

MIT 18.650 Statistics for Applications, Fall 2016

MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathe…

  • Free video
  • 22 videos, 28 hours

Stanford University

AI Luminaries

A curated collection of videos featuring top experts in artificial intelligence.

  • Free video
  • 20 videos, 15 hours

Stanford University

Generative AI Program

-Learn more and enroll in the program: https://online.stanford.edu/programs/generative-ai-technology-business-and-society-program Recent advancements in generative AI are reshaping industries, pushing technological boundaries, and revolutionizing creative processes. In this fast-changing landscape…

  • Free video
  • 24 videos, 2 hours

Stanford University

Artificial Intelligence

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Delve into the exciting world of Artificial Intelligence with insights and research from the world's top experts. This playlist offers a comprehensive journey, from foundational machine learning con…

  • Free video
  • 187 videos, 142 hours

Stanford University

Stanford CS229: Machine Learning led by Andrew Ng | Autumn 2018

Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…

  • Free video
  • 21 videos, 28 hours

Massachusetts Institute of Technology

MIT 6.034 Artificial Intelligence, Fall 2010

View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabili…

  • Free video
  • 30 videos, 24 hours