Cultivating AI Mindset
AI Training Curriculum to Students for After School Club / ECA
Overall Aim:
A K-12 curriculum designed under the IB framework that empowers students with a deep understanding of Large Language Models (LLM) and multimodal AI capabilities. The curriculum progresses from conceptual exploration and interactive visual tools (MYP) to code-level practice and real-world application development (DP).
Exploring the World of AI (Middle School / MYP)
(16-20 weeks, 90-minute sessions)
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Weeks 1-4
Foundations & Interactive Exploration
• Introduction to AI & LLM:
• Understand core AI concepts and explore everyday applications.• Learn how Large Language Models acquire language proficiency from vast data sets.• Interactive Tools:
• Engage with visual platforms (e.g., Machine Learning for Kids) to observe model training and behavior.• Participate in activities that illustrate pattern recognition and language prediction. -
Weeks 5-8
Mastering Prompt Engineering
• Prompt Engineering:
• Develop foundational skills in designing effective prompts.• Advance to techniques such as Few-shot and Chain-of-Thought prompting for improved output control.• Applications in Writing & Translation:
• Conduct hands-on exercises with tools like ChatGPT and DeepSeek.• Generate creative writing, summaries, and translations to understand practical uses of LLMs. -
Weeks 9-12
Expanding Applications & Ethical Considerations
• Broader AI Applications:
• Explore AI-assisted coding, creative storytelling, and automated information summarization.• Analyze real-world scenarios to see how AI augments various learning tasks.• Ethics & Safety:
• Discuss AI bias, misinformation risks, and the importance of responsible usage.• Engage in debates and case studies to develop critical perspectives on ethical AI. -
Weeks 13-16
Multimodal Innovation
• Image Generation: Experiment with text-to-image tools (e.g., DALL·E, Stable Diffusion) to generate visual content.• Voice & Music Synthesis: Practice using Text-to-Speech (TTS) tools and explore AI-driven music creation.• Video Generation: Examine the challenges and potentials of AI-generated video content. -
Capstone Project
• Collaboratively design and develop an AI assistant prototype that integrates multimodal outputs—text, images, voice, and video.
• Present projects to peers, highlighting the design process, technical challenges, and ethical considerations.

Advanced LLM Application Development
(High School / DP)(16-20 weeks, 90-minute sessions)
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Weeks 1-4
LLM Fundamentals & Advanced Prompting
• Course Introduction & LLM Overview:
• In-depth exploration of Transformer architectures, training processes, and data challenges.
• Discussion on the evolution and current state-of-the-art in LLMs.
• Advanced Prompt Engineering:
• Learn sophisticated techniques to optimize LLM responses in complex scenarios.
• Analyze real-world examples and experiment with different prompt formulations.
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Weeks 5-8
Coding, API Integration & Retrieval-Augmented Generation (RAG)
• Coding & API Integration:
• Hands-on sessions using Python to interact with LLM APIs (e.g., OpenAI).
• Focus on parameter tuning, error handling, and output evaluation.
• RAG (Retrieval-Augmented Generation):
• Understand how to combine real-time data retrieval with LLM generation to enhance answer quality.
• Implement prototype workflows that integrate external knowledge sources.
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Weeks 9-12
Model Fine-Tuning & Capstone Project Planning
• Model Fine-Tuning:
• Explore concepts and practical techniques for fine-tuning a pre-trained LLM for specialized tasks.
• Engage in hands-on exercises, including data preparation and iterative training.
• Team Project Planning:
• Initiate a capstone project where teams propose a real-world AI application leveraging LLMs.
• Develop project proposals covering technical approach, ethical considerations, and feasibility.
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Weeks 13-16
Multimodal Integration
• Image & Visual Content Generation:
• Integrate APIs like DALL·E or Stable Diffusion to generate dynamic visual content.
• Audio & Video Synthesis:
• Develop skills in text-to-speech (TTS) and explore basic video creation/editing techniques.
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Capstone Project
• Teams develop and refine a comprehensive AI application that integrates text, image, voice, and video outputs.• Final presentations include a live demo, detailed documentation, and a project defense session.


Rhoda Chen
Contact Rhoda for Immediate support and information