AI Engineering Bootcamp - Python

Classwork and projects from an AI Engineering course covering multi-agent systems, vector databases, and agent architectures.

Structure

Each class session has its own directory with isolated dependencies:

• session-1/ - Session 1 classwork
• session-2/ - Session 2 classwork
• (more sessions to be added)

Requirements

• Python >= 3.14
• uv (Python package manager)

Setup

1. Clone the repository
2. Copy .env.example to .env and add your API keys:

   cp .env.example .env
   # Edit .env with your actual API keys

3. The .env file is shared across all sessions - no need to duplicate keys!

Working with Sessions

Each session directory is self-contained:

# Navigate to a session
cd session-1

# Install dependencies for that session
uv sync

# Run the code
python main.py

Development Workflow

1. Work in the specific session directory
2. Commit changes from the repository root:

   cd /path/to/ai-engineering-bootcamp-python
   git add session-x/
   git commit -m "feat: Complete session-x exercises"
   git push