Month 1 — Data & Patterns:
Session 1: What is machine learning? Supervised vs unsupervised
Session 2: Training data — garbage in, garbage out
Session 3: Classification — teach a model to sort cats and dogs
Session 4: Regression — predict a number from data

Month 2 — How Models Learn:
Session 5: Features — what information does the model see?
Session 6: Overfitting — why memorising is not learning
Session 7: Test sets — how we know if a model is good
Session 8: Hands-on — train a model on Teachable Machine

Month 3 — AI in the Real World:
Session 9: Recommendation engines — how Netflix knows
Session 10: Natural language processing — reading and writing AI
Session 11: Why AI fails — bias and bad data in Indian context
Session 12: Build and present your own trained image classifier