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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