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.
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
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What you get
6 modules and 42 hands-on lessons with runnable code, failure diagnosis, and measured comparisons
2 capstone repositories you build, test, evaluate, and keep as portfolio proof
Videos, source code, complete projects and architecture diagrams
Recordings of live sessions
Discord community access
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