Advanced Concepts of Modelling in AI Class 10 Unit 2 | One Shot | CBSE AI Code 417 | Rohit Singh скачать в хорошем качестве

Advanced Concepts of Modelling in AI Class 10 Unit 2 | One Shot | CBSE AI Code 417 | Rohit Singh

🧠 Advanced concepts of modelling in AI Class 10 Unit 2 explained in one focused, exam-ready session—for students who want clarity over chaos. This one-shot lecture follows the official CBSE syllabus and PDF notes and explains how AI models are built, trained, and trusted—from rule-based logic to learning-based intelligence. ✘ No fluff ✘ No shortcuts ✔ Board-aligned understanding You’ll decode: ➤ AI vs ML vs DL (not buzzwords—structure) ➤ Supervised, Unsupervised & Reinforcement Learning (when & why) ➤ Classification vs Regression (exam traps cleared) ➤ Clustering & Association (hidden patterns revealed) ➤ Perceptron Model—weights, bias & decisions explained like real life 👨‍🏫 Instructor Rohit Singh 🎓 PGT Computer Science | 10+ years of board-focused teaching 📘 CBSE Specialist: AI (417) | CS (085) | IP (065) 🏫 Classes 📍 Offline: Sant Nagar & Hudson Lane 📞 Counselling & Enrolment: 8800873871 🔗 Study Resources & Community ▪ 📘 Notes & PDFs → www.SinghClasses.in ▪ 💬 WhatsApp Group → chat.whatsapp.com/LW4dBrAHIaGAXwK1ni2MPH 📌 What You’ll Learn ✔ Meaning of Modelling in AI ✔ Rule-Based vs Learning-Based approaches ✔ Clear AI vs ML vs Deep Learning comparison ✔ Supervised Learning → Classification & Regression ✔ Unsupervised Learning → Clustering & Association ✔ Reinforcement Learning → reward–penalty logic ✔ Neural Networks → ANN & CNN basics ✔ Perceptron Model → weights, bias & threshold ✔ CBSE-style Test Yourself MCQs 📝 🎓 Who This Is For 👨‍🎓 Class 9–12 CBSE (AI 417, CS 085, IP 065) 🎯 BCA / MCA / BTech / MTech aspirants 📱 Students studying primarily on mobile 📣 Before You Leave 👍 Like if this cleared your confusion 💬 Ask doubts in comments (I reply) 🔔 Subscribe for complete CBSE AI coverage 📤 Share with a friend stuck on Unit 2 ❓ Think & Comment If you had to predict your board exam score, would you use ➊ Classification or ➋ Regression — and why? ⏱️ Timestamps | Study Smart, Not Long ━━━━━━━━━━━━━━━━━━ 00:00 – Introduction | Unit 2 Weightage (11 Marks) 00:57 – AI vs ML vs DL (Clear Comparison) 04:10 – Neural Networks | ANN & CNN 06:23 – AI Modelling Terminologies 09:35 – Modelling in AI | Full Overview 11:02 – Rule-Based Learning 13:15 – Learning-Based Models 15:10 – Supervised Learning | Classification & Regression 17:15 – Unsupervised Learning | Clustering & Association 18:24 – Test Yourself 1 20:06 – Reinforcement Learning Explained 21:13 – Parts of Supervised Learning 23:10 – Parts of Unsupervised Learning 25:51 – Test Yourself 2 27:34 – Perceptron Model | Neural Network Basics 33:40 – Test Yourself 3 41:48 – Outro – Subscribe, Like & Share ━━━━━━━━━━━━━━━━━━ 🔖 Hashtags #CBSEClass10AI #AI417 #AdvancedConceptsOfModelling #MachineLearningClass10 #NeuralNetworks #PerceptronModel #ReinforcementLearning #BoardExamAI #RohitSingh #SinghClasses