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Course Proposal

Title: Building Intelligent Agents with Generative AI and LangCHain

We have been asked to lead a team of students from the University of Minnesota EECS department in a senior seminar on the use of generative AI to solve specific problems. Our focus will be on prompt engineering, LangChian, chatbots, and the design of intelligent agents.

Students have the flexibility to pick problems that are relevant to their interests, but the generation of content for software and lesson plan generation is strongly encouraged. Specifically, we will be demonstrating the use of ChatGPT to create MicroSimulations for use in the classroom.

Student Prerequisites

  1. Intermediate Python coding skills
  2. Basic knowledge of GitHub
  3. Knowledge of how to run UNIX Shell commands from a terminal
  4. Approximately 60 hours of time
  5. Each student should have access to the OpenAI ChatBot Pro tools ($20/month)

Process

  1. We will have an initial lecture that will focus on generative AI and the use of ChatGPT

  2. Students who choose to participate will be assigned to teams of five people.

  3. Each team will be asked to create a document that clearly outlines the goals of their project, such as developing a website that utilizes generative AI (like ChatGPT) to personalize educational content. Ensure these objectives align with the curriculum and learning outcomes. The focus of this document is what the program should do without regard to how it will do it.

  4. Teams will draft a six-week plan where students each person spends 10-hours per week. The plan will break the project into smaller, manageable milestones. This could include initial research, design phase, coding, testing, and final presentation.

  5. Each team will be responsible for creating a website using GitHub pages and mkdocs. A significant portion of the assessment will be made on the quality of this website.

Responsibility of Dan McCreary

  1. Provide overall outlines of the course content and goals
  2. Assist students in getting their Python development environment working (excluding PC administration)
  3. Deliver key lectures and maintain content to the online Python and LangChain tools
  4. Assist students in getting their Markdown content on their GitHub Pages
  5. Assisting in assessment when appropriate

Learning Objectives

At the end of this course, students will:

  1. understand the capabilities of deep neural networks to generate content
  2. be familiar with the skills involved in prompt engineering
  3. know the steps to create a website with GitHub Pages
  4. know how Markdown language is used to hold content
  5. understand the role of generative AI in creating chatbots and agents
  6. be aware of and have an appreciation of the rate of change of tools such as LangChain
  7. appreciate the role of the open-source community in the creation of new AI tools

Assessment

  1. 50% is how your fellow students rate your participation
  2. 20% is the quality of the final product
  3. 20% is the quality of the code and documentation
  4. 10% can parts of the system be leveraged by future students (reusable components)