AI と批判的思考ブートキャンプ: 人工知能をトレーニング、テスト、質問しましょう!
中学生が毎週 35 分のセッションで独自のモデルをトレーニングし、バイアスを明らかにし、批判的思考スキルを養う、16 週間の実践的な AI ブートキャンプです。コーディングの経験は必要ありません。
Faruk Hasan
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4.8
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含まれるもの
16 ライブミーティング
9 時間 20 分 授業時間宿題：
週1時間. 週1～2回修了証書
含まれるこの文章は自動翻訳されています
このクラスで学べること
英語レベル - 不明
Beginner レベル向け
Class Experience 🤖✨ --------------------- Live, project-based AI for middle schoolers—35 fun-packed minutes once a week for 16 weeks! Learners discover how artificial intelligence works, why it sometimes fails, and how to question digital info with rock-solid critical-thinking skills. No coding background needed—just curiosity! 🚀 What the 16-Week Adventure Looks Like ------------------------------------------- Discover AI Basics (Weeks 1-4) – Spot hidden algorithms in daily life, gather images, and train a first computer-vision model in Google Teachable Machine. Debug & Question Models (Weeks 5-8) – Break those models on purpose to reveal bias, fairness, and accuracy issues, using beginner-friendly explainable-AI tools. Sharpen Critical Thinking (Weeks 9-12) – Tackle fact-checking challenges, identify deepfakes, and apply a claim-evidence-reasoning routine to any online claim. Create & Showcase (Weeks 13-16) – Build an AI-for-Good prototype in Scratch or Teachable Machine export, refine it with peer feedback, and deliver a 90-second showcase pitch. 📅 Weekly Class Flow (35 min) ----------------------------- Hook & Review (5 min) – meme, poll, or lightning video to spark curiosity. Mini-Lesson & Live Demo (12 min) – slides + real-time model training; learners answer via mic or chat. Hands-On Practice (12 min) – group experiment (e.g., tweak a dataset, test for bias). Reflection & Exit Ticket (6 min) – share screens, post one “Aha!” and one question. I stay 5 minutes after each class for open Q&A and return journal feedback within 24 hours. 🎮 Teaching Style & Interaction ------------------------------- Inquiry-first & conversational – every learner speaks, chats, or screen-shares each session. Show-and-Do pacing – never more than 5 minutes of “listen only.” Gamified checks – Kahoots, live polls, and “bias-debugging” races keep energy high. 🏠 Optional At-Home Practice (20-30 min/week) Collect new images or sounds Add to your reflection journal Iterate on the capstone project – all browser-based & family-friendly. 🌟 Outcome ------------ By Week 16, each learner will have trained, tested, and critiqued their own AI project, confidently using terms like machine learning, algorithmic bias, and model accuracy—skills that help them thrive in today’s AI-powered world.
学習到達目標
Explain the difference between a rule-based algorithm and a machine-learning model, citing everyday examples of each.Explain the difference between a rule-based algorithm and a machine-learning model, citing everyday examples of each.
シラバス
16 レッスン
16 週間以上レッスン 1:
Meet AI: Algorithms vs. Models
Kick-off with a hands-on card game to see how rule-based code differs from machine-learning models; learners identify AI they already use. 35 分のオンラインライブレッスン
レッスン 2:
Collect & Label Data
Best practices for gathering balanced images or sounds; students start building a personal dataset. 35 分のオンラインライブレッスン
レッスン 3:
Accuracy & Confidence
Read model metrics, test edge cases, and learn the difference between a good guess and a lucky one. 35 分のオンラインライブレッスン
レッスン 4:
Bias Detective I: Sampling & Fairness
Intentionally skew a dataset to watch accuracy plummet and discuss real-world fairness issues. 35 分のオンラインライブレッスン
その他の情報
受講の前提条件
Learners should be comfortable with basic computer operations—opening a browser tab, using a webcam, and typing in chat. No coding experience is required; all AI tools we use are drag-and-drop or guided by the teacher.
外部リソース
学習者は、Outschoolが提供する基本ツール以外のアプリやウェブサイトを使用する必要はありません。
参加しました May, 2020
4.8
152レビュー
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教師の専門知識と資格
修士号 Loyola Marymount Universityから
I’m a Software Development Engineer in Testing with 6 + years building and testing AI-powered software in finance, healthcare, and ed-tech, where I train models, run bias checks, and write automated test suites in Python and TypeScript.
On the teaching side, I’ve delivered 300 + live Outschool hours in Python, web dev, and intro AI, mentor a middle-school robotics team, and teach GED math and computer literacy at CUNY LaGuardia. These roles keep me fluent in turning complex tech into hands-on, age-appropriate lessons that help learners build and question real AI systems.レビュー
ライブグループコース
$10
毎週週に1回、 16 週間
35 分
オンラインライブ授業
年齢: 11-14
クラス人数： 2 人-6 人
