The AI Engineer's Toolkit

7 lessons

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Setup Your Environment

Stop fighting dependency hell. Master the modern, high-speed Python workflow using uv, Docker, and Git. Initialize your workspace and verify it with a data processing test.

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You cannot build robust AI systems on a fragile foundation.

As a developer, you can lose hours fighting "dependency hell" - conflicting Python versions, broken environments, and the classic "it works on my machine" bug. Let's skip that phase entirely.

In this tutorial, you will configure a real-world development environment. We are discarding legacy tools for the modern high-speed stack: uv for instant package management, Docker for production parity, and Git for version control.

This is the foundation that will power every project you build in this Academy.

Tutorial Goals

  • Understand why Git and Docker are essential for AI development
  • Install the complete command-line toolkit for professional AI engineering
  • Verify everything works with simple commands
  • Build the foundation that every other academy tutorial depends on

Let's Get You Set Up