nonobie — Real dev skills, explained like a friend would

A visual map of the 6 levels and 82 chapters (plus 5 projects). Each level is independently shippable.

Course path — L0 to L5flowchart

Rendering diagram…

L3 (Web Backend) and L4 (Data & AI/ML) both build on L2 (Advanced Python) but can be taken in either order — backend-first if you're -focused, data-first if you're ML-focused. Both feed into L5, which makes you professional-grade at tooling regardless of track.

Difficulty curve

🟢 Beginner (L0–L1) — assumes zero programming experience. Heavy use of analogies and REPL examples. ~24 chapters.
🟡 Intermediate (L2–L3) — assumes L1. Real internals (GIL, asyncio), real deployed APIs. ~30 chapters.
🔴 Advanced (L4) — assumes L2. Full data pipeline + LLM application . ~16 chapters.
🟣 Pro (L5) — assumes L3 or L4. The tooling discipline that separates hobby code from team code. ~12 chapters.

Projects

#	Project	Level	Stack
P1	Expense Tracker (CLI)	L1	Python · dicts/lists · file I/O · argparse
P2	Web Scraper (published package)	L2	asyncio · aiohttp · generators · pyproject.toml · PyPI
P3	Production API	L3	FastAPI · SQLAlchemy · PostgreSQL · · pytest ·
P4	RAG Support Copilot	L4	OpenAI API · LangChain · pgvector · pandas · evaluation harness
P5	Automation Toolkit	L5	pytest · ruff · uv · GitHub Actions · Docker · cron/scheduled jobs

Each project ships with a complete codebase, a runbook, and an architecture-decision record (ADR).

Cross-references to existing courses

To avoid duplication, this course cross-references foundational topics covered elsewhere on the platform:

Topic	See instead
HTTP, client-server, REST theory	Backend-For-Noobie
theory, joins, indexes	SQL-Fundamentals, SQL-Postgres
Auth theory, JWT internals, OAuth flows	ABE L3
Docker, Compose, concepts	ABE L6
LLM fundamentals, embeddings, RAG theory	ABE L7

Each chapter that touches a cross-referenced topic includes a callout pointing back — so you always know whether you should read the upstream chapter first or jump straight in.