Digital Mind Essential AI Foundations for Children 6–10 儿童AI启蒙课(6-10 岁）
Inspired by the Presidential AI Challenge 以总统AI挑战赛为标杆设计的AI课程
It provides a comprehensive AI foundation program for young learners and is designed to build true AI-first thinking from an early age. Ideal for children ages 6–10 with no prior experience. 面向6–10岁零基础儿童，培养真正的AI底层思维能力，是系统化AI启蒙课程。
32-Lesson Digital Mind AI Foundations Curriculum 32节《Digital Mind · 儿童AI启蒙课》大纲
Four Learning Modules｜四大模块
- Module 1：AI Fundamentals (Lessons 1–8) — Building an AI Worldview 模块1：AI基础认知（1–8）——建立AI世界观
- Module 2：Computational Thinking & AI Logic (Lessons 9–16) 模块2：计算思维与AI逻辑（9–16）
- Module 3：Data, Models & the Nature of Intelligence (Lessons 17–24) 模块3：数据、模型与智能本质（17–24）
- Module 4：AI Creativity, Ethics & Innovation Projects (Lessons 25–32) 模块4：AI创作、伦理与创新项目（25–32）
Module 1 | Understanding the World of AI (Lessons 1–8) 模块1｜AI世界认知（第1–8课）
- What is AI? Human Intelligence vs Artificial Intelligence 什么是 AI？人类智能 vs 人工智能
- AI in Everyday Life: Phones, Navigation, Voice, Recommendations 生活里的 AI：手机、导航、语音、推荐算法
- How AI Sees: Image Recognition (AI Eyes) AI 会看：图像识别（眼睛AI）
- How AI Hears: Speech Recognition & Synthesis (AI Ears) AI 会听：语音识别与合成（耳朵AI）
- How AI Reads: Language Understanding & Translation AI 会读：文字理解与翻译
- How AI Moves: Robots & Obstacle Avoidance AI 会动：智能机器人与避障
- How AI Chooses: Recommendation Systems AI 会选：推荐系统原理
- Types of AI: Narrow, General, Everyday, Future AI AI 分类：弱AI、强AI、生活AI、未来AI
Module 2 | Computational Thinking & AI Logic (Lessons 9–16)模块2｜计算思维与AI逻辑（第9–16课）
- Sequential Thinking: Step-by-step execution 顺序思维：一步一步执行
- Conditional Logic: If…Then… 判断思维：如果…就…
- Loops: Repetition as AI power 循环思维：重复执行
- Decomposition: Breaking problems down 拆分思维：拆解复杂问题
- Pattern Recognition: Finding rules 模式识别：发现规律
- Error Correction: Why AI makes mistakes 纠错思维：AI为什么会犯错
- Simulation: Mimicking behavior 模拟思维：模仿人类行为
- Flowchart Project: My first AI logic map 逻辑项目：我的AI流程图
Module 3 | Data, Models & Intelligence (Lessons 17–24) 模块3｜数据、模型与智能本质（第17–24课）
- What is Data? Numbers, images, sounds 什么是数据：数字、图像、声音
- Data organization & statistics 数据整理与统计
- What is Training? How AI learns 什么是训练：AI如何学习
- What is a Model? AI brain template 什么是模型：AI“大脑模板”
- Machine Learning: Learning improves performance 机器学习：越学越聪明
- AI Prediction: Guessing outcomes AI预测：预测结果
- Strengths of AI AI优点：快、准、不累、持续学习
- Limitations of AI AI局限：无情感、依赖数据
Module 4 | AI Innovation & Ethics (Lessons 25–32) 模块4｜AI创作、伦理与项目（第25–32课）
- AI Art: Understanding creativity AI绘画：理解艺术
- AI Music & Voice Generation AI音乐与配音
- AI for Good: Real-world applications AI公益应用
- AI Safety: Privacy & misinformation AI安全：隐私与信息识别
- AI Ethics: Responsibility & fairness AI伦理：责任与公平
- Future AI: Smart cities 未来AI：智能城市
- Innovation Project Design 创新项目设计
- Final Presentation & Defense 期末展示与答辩训练