As I started my journey into AI and Data Science, I quickly realized that managing Python environments can be a total headache. Between broken dependencies and 'it works on my machine' errors, I was spending more time troubleshooting my setup than actually writing code. I wanted a way to streamline my workflow and keep my machine clean, so I moved to a Miniconda + Homebrew setup on my Mac. To save myself (and hopefully you) from digging through endless documentation, I condensed the 'essential' commands into a single, high-density A4 infographic. This cheatsheet skips the legacy bloat and focuses on a production-first workflow: Clean Installation: Setting up via Homebrew for macOS. Environment Hygiene: Creating, cloning, and exporting environments so your projects stay isolated. Jupyter Integration: Properly registering kernels so your notebooks actually see your installed packages. The Workflow: A step-by-step checklist for starting any new project the right way.…