Day 12 Prompts
Hour 1: Collaborative filtering demo
👉 “Explain step-by-step how collaborative filtering works in AI recommendation systems with a simple demo using Python and sample data.”
Hour 2: Add 20 sample products
👉 “Generate 20 unique sample product entries (with name, category, description, and price) for an online AI-powered e-commerce store.”
Hour 3: Rating & review system
👉 “Write Python code to build a simple rating & review system where users can give 1–5 star ratings and leave short feedback for products.”
Hour 4: Product promotion ad
👉 “Create an engaging promotional ad (text + tagline + hashtags) for an AI product recommender tool that helps customers find the right items.”
Hour 5: Blog 12 – AI Product Recommender
👉 “Write a 600-word blog post on the topic: ‘AI Product Recommender: How Machines Help Us Shop Smarter’ with intro, benefits, working, and conclusion.”
Hour 6: Take notes from webinar
👉 “Summarize key notes from a webinar about AI-driven personalization in e-commerce, highlighting benefits, challenges, and future trends.”
Hour 7: Give feedback
👉 “Write constructive feedback (positive + suggestions for improvement) for a team member who created a basic recommender system prototype.”
Hour 8: Learn about edge AI
👉 “Explain what Edge AI is, how it differs from cloud AI, and provide 3 real-world use cases where Edge AI is applied in recommendation systems.”