Start Here
Most AI courses jump straight to prompting and agents. Production AI engineering requires Python, Git, Linux, HTTP, databases, Docker, and CI/CD. Phase 0 fills that gap so Phase 1+ makes sense instead of feeling like magic.
Phase 0 is learning to drive before entering a highway — you need steering, brakes, and mirrors before merging into fast AI traffic.
Visual Workflows
Start here — study each diagram, then use + / − to zoom if needed.
Overview
Scroll inside the frame · use + / − to zoom
Scroll inside the frame · use + / − to zoom
Key Takeaways
- 1.Phase 0 is the engineering foundation every AI builder needs before touching LLMs, RAG, or agents — it teaches the tools and concepts behind every production AI system.
- 2.You will not master every topic here on day one.
- 3.The goal is familiarity: know what each tool does, when to use it, and where to look when something breaks.
- 4.Each module follows the same format — concept bullets, why it matters, analogy, visual diagram, example, practice task, commands, and cheat sheet.
- 5.Study in order when you are new; skip modules you already know and return to the cheat sheets when needed.
Real Example
Scenario
You are new to programming and want to build an AI chatbot eventually.
What you would do
Start with Python and Git, then HTTP and JSON (because every LLM API uses them), then Docker and SQL when you deploy. Skip deep mastery of Linux networking until you hit a real bug — but read the cheat sheets so you know where to look.
Practice Task
Open the Python module next. Skim its diagram and cheat sheet, then come back here after finishing all 14 modules to confirm you can explain why each one exists in one sentence.
Commands
Commands to Remember
Open one module per study session # do not rush through all 14 at onceRun every command in Commands to Remember # typing beats readingBookmark cheat sheets # revisit when building real projectsgit checkout -b phase-0-practice # practice in a safe branchpython -m venv .venv && source .venv/bin/activate # set up practice environment
Cheat Sheet
Quick recap
quick ref- •Phase 0 = engineering base before AI — not optional for production work
- •Goal is familiarity, not mastery — revisit cheat sheets when building
- •Study order: Python → Git → Linux → CLI → Networking → HTTP → REST → JSON → Docker → SQL → NoSQL → Testing → CI/CD
- •Per module: bullets → why → diagram → example → practice task → commands → cheat sheet
- •Skip modules you know; never skip HTTP, JSON, and Git
- •Phase 1 (GenAI) assumes you understand HTTP requests and JSON responses
- •Build the Phase 0 projects (REST API, Docker, Git workflow) to connect everything
- •~3 hours per module if new · ~30 min skim if experienced
Common Mistakes
- ✕Skipping Phase 0 and jumping to agents — then not understanding API errors or deployment
- ✕Trying to memorize every command instead of knowing where to look
- ✕Reading without running commands in the terminal
- ✕Expecting Phase 0 to teach Python from zero — use external practice for deep coding skill