🏆Capstone — Build & Present
Bring it all together into one AI-powered project.
📖 Key concepts
- Define a problem & dataset
- Build: data → model/logic → result
- Evaluate honestly
- Present clearly (demo + story)
💻 Try this code
# Pick ONE:
# 1) Classifier (e.g., spam / sentiment / iris-style)
# 2) Predictor (regression on a real CSV)
# 3) LLM app (summariser / Q&A / study buddy via an API)
# Ship it. Demo it. Explain your choices.👥 Learn it your way
🧒 Young Explorers
Make something you’re proud to show your family — a real AI you built!
Build a small AI helper (quiz buddy, mood detector, or recommender) and demo it.
💼 Professionals
Treat it like a portfolio piece: clean repo, README, metrics, and a 3-minute demo.
Ship an end-to-end mini-app: data in → model/LLM → useful output, with a short write-up.
You’ve gone from print("hello") to building and reasoning about AI in 30 days. This capstone is proof — and the start of your AI journey.
Choose a classifier, a predictor, or an LLM app. Build it end-to-end (data/input → model or API → useful output), evaluate it honestly, and present a short demo explaining your choices, results, and limitations.
✅ Quick check
What three things make a great capstone demo?
A clear problem, an honest evaluation, and a clear presentation.