HKUST UPC – AI Coding (6-10 years old) – Level 3

Eligibility: For HKUST alumni/staff families who can join HKUST UPC.

This course is offered for HKUST UPC members. If you are HKUST staff or alumni and are not currently a UPC member, you may apply/renew here: https://upc.hk/membership.

Held at HKUST campus – Room 2129C

Course Schedule

Course Overview

Level 3 introduces “vibe coding” where AI generates and refactors code in real-time, emphasizing collaboration between young developers and AI, with mastery of prompts and system integration as key skills alongside traditional programming. Students transition from AI creators to AI entrepreneurs, learning to build sophisticated AI applications that solve real-world problems while mastering prompt engineering, becoming “AI-assisted developers” who are incredibly valuable because they know how to guide and quality-check AI’s work.

This advanced level integrates actual Python coding, professional prompt engineering techniques, AI ethics, and competitive project development. Skills related to AI and machine learning will be in high demand, and kids equipped with these skills will have a competitive edge in the future job market. Students will work with cutting-edge tools including ChatGPT, Python programming environments, real AI APIs, and deployment platforms—all while maintaining age-appropriate content and instruction.

Learning Outcomes 🎯

By the end of this elite-level AI program, students will:

Advanced AI Engineering:

• Master prompt engineering fundamentals including the skill of asking AI tools the right question or command to get the best response
• Write actual Python code to build AI-powered applications
• Integrate multiple AI APIs (text generation, image creation, voice synthesis) into single projects
• Deploy functioning web applications accessible to real users
• Understand and implement “vibe coding” workflows with AI assistants

Entrepreneurial & Problem-Solving Skills:

• Identify genuine problems in their community and design AI solutions
• Create comprehensive project proposals with business value propositions
• Build minimum viable products (MVPs) and iterate based on testing
• Present polished demos of their work
• Develop competitive portfolios showcasing deployed projects

Professional Coding Foundations:

• Write clean, commented Python code following professional standards
• Debug AI-generated code and improve its quality
• Use version control basics (simplified Git concepts)
• Implement error handling and user input validation
• Understand how to read and modify API documentation

Advanced Prompt Engineering:

• Develop detailed and effective AI prompts using techniques such as identity prompts, quality boosters, and descriptive modifiers
• Master chain-of-thought prompting for complex problem-solving
• Create prompt templates for repeated tasks
• Understand token limits and optimize prompts for efficiency
• Implement reverse prompt engineering to improve AI outputs

Ethical AI Leadership:

• Recognize and mitigate algorithmic bias in AI tools for kids
• Design inclusive datasets that represent diverse populations
• Understand data privacy and implement safe practices
• Make informed decisions about appropriate AI use cases
• Lead discussions on responsible AI development

8-Week Elite Curriculum 📚

Week 1: Welcome to Professional AI Development 💻🔥

Core Concepts:

• Introduction to professional development workflows
• Python fundamentals review and AI integration
• Setting up development environments
• Introduction to AI-assisted coding (“vibe coding”)
• Professional prompt engineering frameworks

Hands-On Activities:

• Python AI Setup Studio: Install and configure Python, VS Code (or browser-based IDE like Replit), and essential libraries. Create first “Hello AI World” program that calls an AI API.
• Prompt Engineering Mastery Lab: Write better prompts like “Write a bedtime story about a girl who finds a robot dragon in her backyard. Make it funny and 200 words long” and “Create a 5-question quiz for 10-year-olds about space. Each question should have 3 answer choices and one correct answer.”
• AI Code Assistant Challenge: Learn to use AI to generate Python code snippets, then debug and improve the AI’s suggestions. Understand when AI helps and when human judgment is needed.
• Professional Portfolio Setup: Create GitHub-style portfolio page to showcase all Level 3 projects with descriptions, screenshots, and reflection notes.
• Competitive Coding Introduction: Explore age-appropriate coding challenges and learn how AI can assist (but not replace) problem-solving skills.
• Real-World API Explorer: Make first successful API calls to free AI services (text generation, image analysis) and understand request/response structures.
• Learning Focus: Transition from visual tools to text-based coding while maintaining confidence; establish professional habits for the advanced journey ahead.

Week 2: Advanced Prompt Engineering & AI Content Creation 🎨✍️

Core Concepts:

• Advanced prompting techniques (few-shot, chain-of-thought, role-based)
• Content generation with AI (text, images, music)
• Prompt templates and reusability
• Quality evaluation of AI outputs
• Combining multiple AI tools in workflows

Hands-On Activities:

• Prompt Engineering Competition: Students compete to create the most effective prompts for specific tasks, learning techniques like specificity, context setting, and output formatting.
• AI Storytelling Engine: Build Python program that uses advanced prompts to generate choose-your-own-adventure stories with consistent characters and plot threads.
• Multi-Modal Content Creator: Use free AI tools to generate custom images and music by applying fundamental AI prompt engineering principles, then combine them into cohesive projects.
• Prompt Template Library: Create reusable prompt templates for common tasks (homework help, creative writing, quiz generation, idea brainstorming) with proper documentation.
• AI Art Gallery Project: Generate series of themed AI artworks using progressively refined prompts, documenting the iteration process and learning from failures.
• Content Quality Evaluator: Develop critical skills to assess AI-generated content for accuracy, bias, appropriateness, and usefulness.
• Learning Focus: Prompt craft, integration thinking, and design judgement as essential skills for AI-powered development.

Week 3: Python AI Programming Fundamentals 🐍🤖

Core Concepts:

• Python basics: variables, data types, functions, loops
• Working with AI libraries (simplified versions)
• API integration and authentication
• Error handling and debugging AI applications
• Code organization and documentation

Hands-On Activities:

• Python Accelerator Bootcamp: Create more advanced Python projects much more quickly by working with AI, aka Vibe coding, where AI assists in writing code while students guide and refine.
• AI Chatbot Builder: Create simple command-line chatbot using Python and AI API that maintains conversation context and personality.
• Code Debugging Detective: Practice debugging both student-written and AI-generated code, understanding common errors and how to fix them systematically.
• API Integration Workshop: Successfully connect to multiple free AI APIs (text, image, data analysis), handle responses, and display results in user-friendly formats.
• Smart Calculator Project: Build calculator that uses AI to understand natural language math problems (“what’s 15% tip on $47?”) and solve them programmatically.
• Function Factory Challenge: Create library of reusable Python functions for common AI tasks (send prompt, process response, save results) with clear documentation.
• Learning Focus: Build solid Python foundation while learning how AI tools can accelerate coding; understand that knowing how code works is essential even when AI helps write it.

Week 4: Building Real-World AI Applications 🌍💡

Core Concepts:

• Identifying genuine problems worth solving
• User research and requirements gathering
• MVP (Minimum Viable Product) development
• User interface design for AI applications
• Testing and iteration cycles

Hands-On Activities:

• Problem Discovery Workshop: Research real problems in their school, home, or community through interviews and observation. Document potential AI-powered solutions.
• AI Application Ideation: Brainstorm, sketch, and pitch AI application ideas. Receive feedback and select most viable concepts for development.
• User Story Creator: Write user stories describing how people would use their AI applications. Create simple wireframes showing interface designs.
• Rapid MVP Builder: Build first working version of chosen AI application—doesn’t need to be perfect, but must demonstrate core functionality.
• User Testing Session: Test MVP with classmates acting as users. Document feedback, bugs, and improvement ideas using structured methods.
• Iteration Sprint: Improve application based on testing feedback. Learn that professional developers constantly iterate and refine.
• Learning Focus: Apply design thinking to AI development; understand the complete product development cycle from problem identification to deployed solution.

Week 5: Advanced AI Integration & Deployment 🚀🌐

Core Concepts:

• Multi-model AI integration (combining different AI capabilities)
• Web deployment basics (making apps accessible online)
• Data persistence and user accounts (simplified)
• Performance optimization
• Professional presentation of technical projects

Hands-On Activities:

• Multi-AI Orchestrator: Build application that combines text AI, image AI, and voice AI into single coherent experience (e.g., AI tutor that explains concepts with voice, shows diagrams, and answers questions).
• Web Deployment Workshop: Deploy Python AI applications to free hosting platforms (Streamlit Cloud, Replit, Glitch) so they’re accessible via web browser from anywhere.
• Data Management System: Implement simple data storage so AI applications remember user preferences, conversation history, or generated content across sessions.
• Performance Optimizer: Learn to optimize AI applications for speed and cost (using caching, reducing API calls, implementing loading indicators).
• Professional Demo Preparation: Create polished demonstrations of AI applications including intro slides, live demos, and explanation of technical decisions.
• AI Application Showcase: Present deployed, working AI applications in professional-style pitch format.
• Learning Focus: Transform projects from local experiments to deployed applications that real users can access; develop presentation skills for technical work.

Week 6: Competitive AI Challenges & Hackathon 🏆⚡

Core Concepts:

• Competitive programming with AI assistance
• Hackathon methodologies and team collaboration
• Rapid prototyping under time constraints
• Judging criteria for AI competitions
• Incorporating feedback quickly

Hands-On Activities:

• Mini-Hackathon Day: Full-session hackathon where students (individually or in pairs) build AI applications from scratch addressing specific challenge themes.
• AI Competition Simulator: Participate in age-appropriate AI coding challenges with rankings, time limits, and competitive elements that push skills to next level.
• Speed Coding Challenges: Series of timed challenges where students must build specific AI features quickly using vibe coding techniques.
• Peer Code Review: Learn professional code review practices by examining classmates’ code, providing constructive feedback, and defending their own technical choices.
• Competitive Portfolio Builder: Document all competitive projects with technical explanations, demonstrating growth and problem-solving approaches.
• AI Ethics Hackathon Round: Special challenge focused on building AI tools that address ethical issues (bias detection, accessibility, digital wellbeing).
• Learning Focus: Develop competitive edge while maintaining collaborative spirit; learn to perform under pressure while producing quality work.

Week 7: AI Entrepreneurship & Real-World Impact 💼🌟

Core Concepts:

• Business thinking for AI solutions
• Pitching AI products to stakeholders
• Understanding user needs and market fit
• Social entrepreneurship with AI
• Sustainability and scaling considerations

Hands-On Activities:

• AI Startup Simulator: Develop complete “business plan” for AI application including problem statement, solution description, target users, and impact metrics.
• Customer Interview Workshop: Conduct structured interviews with potential users (classmates, family, teachers) to validate problem and solution fit.
• Pitch Deck Creator: Build professional presentation pitching their AI solution with slides covering problem, solution, demo, impact, and future vision.
• Investor Pitch Practice: Present AI startup pitches to panel of “investors” (teachers, parents, local entrepreneurs) and respond to questions.
• Social Impact Assessment: Evaluate how their AI applications could make positive social impact and identify potential negative consequences to mitigate.
• Scaling Strategy Session: Think through how their AI solutions could serve more users, handle more data, or expand to related problems.
• Learning Focus: Combine technical skills with entrepreneurial thinking; understand that great AI applications solve real problems for real people.

Week 8: Grand Finale – AI Innovation Expo & Certification 🎓🎊

Culminating Achievement Event:

• Live Application Demonstrations: Each student presents working, deployed AI application accessible via web, explaining technical architecture, design decisions, and real-world impact.
• Technical Deep-Dive Presentations: Students explain their code, show how they used AI assistance, demonstrate prompt engineering techniques, and discuss challenges overcome.
• Peer Recognition Ceremony: Students nominate and vote for achievements in categories: Most Innovative Solution, Best Technical Implementation, Greatest Social Impact, Most Improved Developer, Best Prompt Engineer.
• Portfolio Showcase: Display comprehensive portfolios documenting complete Level 3 journey with code repositories, deployed applications, and reflection essays.
• Level 3 Certification Ceremony: Award certificates recognizing completion of advanced AI development training, with specific skill badges earned (Python Programming, Prompt Engineering, AI Ethics, Deployment, Entrepreneurship).
• Pathway to Level 4 Preview: Introduction to even more advanced topics students can explore: machine learning mathematics, neural network fundamentals, AI research methods, advanced algorithms.
• Family Celebration: Parents experience their children’s AI applications firsthand, understanding the sophisticated work accomplished throughout Level 3.
• Learning Focus: Celebrate transformation from AI novices (Level 1) to advanced AI developers and entrepreneurs ready for real-world challenges and continued learning.

Course Features ✨

Professional-Grade Tools (Age-Appropriate Implementation):

• Python Programming: Real Python code using beginner-friendly IDEs (Replit, Thonny, or VS Code with extensions)
• AI APIs: Free tiers of ChatGPT API, Hugging Face models, Stability AI, ElevenLabs (voice)
• Deployment Platforms: Streamlit Cloud, Replit hosting, GitHub Pages (for static content)
• Version Control: Simplified Git concepts using visual interfaces
• Development Environments: Browser-based and local IDEs with AI assistance built-in
• Prompt Engineering Tools: Custom templates, prompt libraries, testing frameworks
• Google’s Teachable Machine that lets kids train their own AI model using their webcam, microphone, or uploaded images with no coding required[1] (integrated with Python projects)

Advanced Learning Methodology:

• AI-assisted coding where generative AI tools help write, debug and optimize code as part of daily workflows[4]
• Project-Based Learning: Every week builds toward deployed, functioning applications
• Competitive Elements: Challenges, hackathons, and friendly competition drive excellence
• Real-World Connection: All projects solve genuine problems with measurable impact
• Portfolio Development: Professional documentation of all work for future showcasing
• Entrepreneurial Mindset: Business thinking integrated throughout technical learning

Comprehensive Skill Development:

• Professional Coding: Writing, debugging, and documenting Python code
• Prompt engineering that gives kids the superpower of guiding smart machines with smart words—it’s the writing skill of the future[1]
• Systems Thinking: Understanding how multiple AI components work together
• Critical Evaluation: Assessing AI outputs for quality, bias, and appropriateness
• Deployment Skills: Making applications accessible to real users worldwide
• Presentation Excellence: Communicating technical work to diverse audiences
• Ethical Leadership: Making responsible decisions about AI development and use

Requirements 📋

Prerequisites:

• Successful completion of Level 2 or demonstrated proficiency in:
  • Creating AI models with Teachable Machine
  • Understanding of basic AI concepts (classification, training, datasets)
  • Comfort with multi-step digital projects
  • Basic problem-solving and debugging skills
• Strong reading comprehension for understanding documentation
• Enthusiasm for learning actual programming

Technical Requirements:

• Computer (laptop recommended; tablets have limitations for coding)
• Reliable internet connection (for API calls and deployment)
• Modern web browser (Chrome, Firefox, or Edge)
• Webcam and microphone for AI training and demos
• Email for account creation on free platforms (Replit, GitHub, Streamlit)

Time Commitment:

• 60-minute live sessions weekly
• (Optional) 1 hour of practice/project work between sessions
• Access to online resources and video tutorials
• Office hours for extra help

Mindset Requirements:

• Persistence when debugging code or troubleshooting errors
• Willingness to iterate and improve based on feedback
• Openness to competitive challenges and learning from peers
• Excitement about building real applications people can use
• Commitment to ethical AI development practices

Duration: 8 weeks, 60 minutes per session
Class Size: Maximum 15 students for personalized attention
Format: Hands-on digital creation with live instructor guidance