# Prerequisite video study guide

This is an intensive prerequisite for facilitators and students. Plan 4–6 hours, including watching, reading, exercises, and the written checks. Complete the required core before enrollment. The optional extensions help a student prepare for a specific track. Links were checked against first-party sites on 2026-09-22; recheck them before a pilot because sites change.

## Required core, about 4 hours

1. **How AI works, 75–90 minutes.** Use Code.org’s [How AI Works](https://code.org/en-US/curriculum/how-artificial-intelligence-works) videos “AI: What is Machine Learning?”, “AI: Training Data & Bias,” “AI: How Neural Networks Work,” and “AI: How Computer Vision Works.” After each video, complete the study log and write what could go wrong. Use captions and the printable transcript route.
2. **Generative AI and verification, 60–75 minutes.** Complete the activities in Code.org’s [Foundations of Generative AI](https://studio.code.org/s/foundations-gen-ai-2024/lessons/1/levels/1/page/1) on input and training data, bias, trust, and the demystifying project. Compare one generated claim with a trusted source. The printed route uses teacher-provided examples.
3. **Systems and problem solving, 45–60 minutes.** Read the English [Artificial Intelligence Foundations course](https://studio.code.org/courses/artificial-intelligence-foundations-2025) overview. Draw an input-process-output-human-check map for one proposed project. No account is required for this reading.
4. **AI literacy and ethics scenarios, 45–60 minutes.** Use the age 11–18 resources in MIT RAISE / Day of AI’s [curriculum collection](https://dayofai.org/curriculum-resources), including “Truth, Tricks, and AI” or “Foundation of Computer Science and AI Systems.” Complete every local ethics scenario check supplied by the program. A facilitator discusses answers and records completion without collecting personal information.
5. **Hands-on test, 45–60 minutes.** Read Google’s [Teachable Machine](https://teachablemachine.withgoogle.com/) “Gather” and “Train” steps, then test two classes of non-identifying classroom objects. Record at least three errors or limitations. If the site is unavailable, sort printed cards and discuss false positives.
6. **Knowledge check and human review, 30–45 minutes.** Complete the [baseline knowledge quiz](baseline-knowledge-quiz.md), explain missed answers, and retry after feedback. The facilitator confirms the 8/10 readiness threshold with a short conversation. A guardian or school reviewer completes its separate review before enrollment.

## Optional extensions, about 1–2 hours

- Web app: [GitHub Pages quickstart](https://docs.github.com/en/pages/quickstart). Read the steps and draw the path from repository to published page. A facilitator can demonstrate with a local folder instead of asking students to create accounts.
- Engineering and making: MakerBot, [Educator’s Guidebook](https://www.makerbot.com/educators-guidebook/). Read the sections on the print workflow and classroom design thinking. If there is no printer, students complete the design, measurement, slicing-plan, and failure-analysis worksheets without printing.
- Club and business: Day of AI, [Teachers](https://dayofai.org/teachers/), and [professional development](https://dayofai.org/professional-development). Students compare the stated learning goal, audience, resource, and evidence of success for a proposed event or service.

## Study log

| Resource | New term | One claim I can explain | One question or limitation |
|---|---|---|---|
| | | | |
| | | | |
| | | | |

The facilitator checks comprehension by asking the student to explain one term with an example. A student who cannot access the video completes the same log from the linked text or a printed transcript. The same preparation and human review apply to the offline route.