Lesson 0: Introduction
0.1 Welcome 0.2 Office Hours
Lesson 1: Environment
1.1 Welcome 1.2 Python 1.3 Virtual environment 1.4 Git 1.5 Cursor 1.6 OpenAI 1.7 First AI Agent 1.8 AI Agent with OpenAI SDK 1.9 AI Agent Chat Bot 1.10 Plan Your Project 1.11 Plan Your Requirements
Lesson 2: User Interaction
🔒 2.1 Architecture 🔒 2.2 Core Logic as a Service 🔒 2.3 Verify core logic 🔒 2.4 Web Server 🔒 2.5 Command Line Interface 🔒 2.6 Web Interface 🔒 2.7 Debugging the Web Interface 🔒 2.8 Bonus Development Tips 🔒 2.9 Your Project
Lesson 3: Interacting with the World
🔒 3.1 Interacting with the World 🔒 3.2 API for Agents 🔒 3.3 Preparing Product Catalog 🔒 3.4 Building a Product Search API 🔒 3.5 Building a Product Search API 2 🔒 3.6 Enabling the Agent to Use Product Search API 🔒 3.7 Web Interface 🔒 3.8 Structured Output 🔒 3.9 Structured Output 2 🔒 3.10 Structured Output 3 🔒 3.11 Your project
Lesson 4: Remembering and Reasoning
🔒 4.1 Context 🔒 4.2 Core Logic 🔒 4.3 Web Server 🔒 4.4 Multiple Rounds 🔒 4.5 Debugging Session Handling 🔒 4.6 Multiple Rounds Take 2 🔒 4.7 Multiple Clients 🔒 4.8 Multiple Actions 🔒 4.9 Multiple Actions Web
Lesson 5: Deployment
🔒 5.1 Deployment 🔒 5.2 AWS 🔒 5.3 EC2 instance 🔒 5.4 Deploy Server Code 🔒 5.5 Creating a Domain Name 🔒 5.6 Map Domain Name 🔒 5.7 Install Nginx 🔒 5.8 Configure Nginx Reverse Proxy 🔒 5.9 Your own project

Lesson 0.1: Welcome

This course provides a comprehensive introduction to AI agent development, structured into five modules:

  1. Development Environment & Basic CLI Agent: Set up your development environment and create a basic AI agent that interacts through command line interface.

  2. Web Server & Multi-User Interface: Learn to build a web server to serve multiple users through a web interface.

  3. API Integration: Enhance your agent to interact with the real world using APIs, going beyond the built-in knowledge of large language models.

  4. Advanced Features: Implement memory for multi-round user interactions and enable multiple actions per user request.

  5. Deployment: Deploy your AI agent server on Amazon Web Services to make it publicly accessible.

Throughout the course, you'll have the opportunity to work on a student project of your choice, building an AI agent for a subject that interests you or benefits your work. The instructor will be available to answer questions and provide guidance on your project.