Learn by doing
Hands-on labs
No prior AI needed
No prior AI needed
A 6-week, beginner-friendly summer introduction to AI—ideas, hands-on labs, and a project—
no prior experience required.
Features
- No AI background required — Starts from “What is AI?” and builds step by step, without heavy math.
- Hands-on first — Short lessons, then activities: train simple models, try demos, finish mini-projects.
- Friendly tools — Visual, browser-based tools (e.g. Teachable Machine, simple block/code) so setup stays light.
- Real-world connection — Relates to apps you use: search, recommendations, photos, chatbots.
- Ethics & safety — Fairness, privacy, deepfakes/misinformation, and responsible use.
- Weekly milestones — Clear goals so a busy summer still feels doable.
- Capstone project — End with a short project + 5-minute presentation.
- Support — Summary notes, Q&A, and optional office hours so you’re not stuck for long.
Eligibility
- Who it’s for — Typically grades 6–12.
- Prior knowledge — None in AI/ML. Comfortable with a computer, browser, and email.
- Optional — Scratch, simple Python, or extra math is a bonus, not required.
- Time — About 3–4 hours/week live + 2–3 hours practice for ~6 weeks.
- Device — Laptop/desktop with a modern browser; webcam/mic if online.
- Conduct — Safe, respectful use of AI tools and your school/organizer’s rules.
Course curriculum
Hello, AI
- What AI is (and isn’t); myths vs reality
- Where AI appears in daily life
- Words: data, model, prediction, training
- Activity: explore safe demos and discuss
How learning from data works
- Patterns in data; train vs test (intuition)
- Overfitting without heavy math
- Activity: Teachable Machine — train and “break” it on purpose
Computer vision (lite)
- How a model might “see” (high level)
- Limits: lighting, angles, bias in data
- Activity: improve a small image model
Language & chatbots (lite)
- Text as data; LLMs in plain language
- Prompting: clear instructions, safety, fact-checking
- Activity: guided prompts; spot wrong answers
Ethics, safety & society
- Privacy, consent, deepfakes, misinformation
- Fairness and why data matters
- Activity: short case study + discussion
Capstone & next steps
- Tiny project (image or text or creative, with clear rules)
- Build, test, one-page “what I learned”
- Presentations + where to learn next, safely