Join Us on November 2nd, 2024

AI Workshop Title: AI Tutors for All: Building Educational LLMs on a Budget

Description:

This 1-hour workshop introduces students in grades 6-12 to Large Language Models (LLMs) and their applications in education. The session covers both open-source and commercial tools for developing LLM-based tutors and educational aids.

Workshop contents:

1. Overview of Large Language Models and their educational applications

2. Introduction to available tools and resources:

   • Open-source options (e.g., GitHub projects, AnythingLLM)

   • Commercial platforms (e.g., OpenAI’s GPT, Anthropic Claude)

3. Demonstration of a basic LLM-powered educational tool

4. Hands-on activity: Customizing a simple chatbot

5. Discussion of APIs and their role in LLM-based projects

6. Comparison of open-source vs. commercial options

7. Resources for further learning and exploration

No prior programming experience is needed. The workshop aims to provide foundational knowledge and practical exposure to LLM-based educational tools.

Student takeaways:

1. Understanding of LLMs: Students will gain a basic understanding of what Large Language Models are and how they can be applied in educational contexts.

2. Awareness of available tools: Participants will learn about both open-source and commercial tools available for developing LLM-based educational applications.

3. Demonstration observation: Students will watch a live demonstration of how to work with and customize a simple LLM-based tool.

4. API introduction: Students will be introduced to the concept of APIs and their role in integrating LLM capabilities into applications.

5. Resource familiarization: Participants will learn about platforms like GitHub and specific projects like AnythingLLM, providing starting points for their own exploration after the workshop.

6. Cost considerations: Students will understand the trade-offs between using free/open-source tools and commercial options.

7. Ethical awareness: Brief introduction to ethical considerations in AI and LLM use in education.

8. Project inspiration: Students will gain ideas for potential projects they could develop for the upcoming STEM competition.

9. Further learning pathways: Participants will receive guidance on how to continue learning about LLMs and AI in education beyond the workshop.

10. Q&A preparation: Students will be encouraged to note down questions during the session for a potential follow-up or Q&A session.

About the Instructor:

Vincent Sha is the Associate Dean of Information Technology and Operation at Carnegie Mellon University’s Dietrich College. With 25 years of IT experience, he specializes in applying technology to solve problems in research and education.

Vincent leads the adoption of generative AI at Dietrich College, developing CMU’s first approved generative AI-based learning interventions. He’s the Technical Lead of CMU’s Open Forum for AI and has received funding from the Omidyar Network for his work in AI tool creation and adoption. He is an expert in fostering collaborative innovation and driving digital culture in applications in applying and creating LLM powered tools.