A 24-week self-study curriculum · fully free

Become an
AI engineer
from scratch.

No bootcamps. No $3,000 courses. Just the best free resources on the internet, sequenced correctly, with a knowledge graph to tie every concept together.

Start week 0 → See the roadmap ↓
24
weeks
10
phases
175+
concept notes
21
projects shipped
$0
total cost
01 / ROADMAP

From linear algebra to shipped agent.

PHASE 00
Toolchain & Mindset
WEEK 0
Python, uv, VS Code, Git, Obsidian, Docker. Zero-friction setup.
PHASE 01
Python & CS
WEEKS 1–2
CS50P, idiomatic Python, NeetCode, Git workflow. The floor you build on.
PHASE 02
Math for ML
WEEKS 3–4
Linear algebra, calculus, probability, information theory. Enough to read papers.
PHASE 03
Classical ML
WEEKS 5–6
Regression, trees, SVMs, clustering. Full lifecycle on tabular data.
PHASE 04
Deep Learning
WEEKS 7–9
Karpathy's Zero-to-Hero. Micrograd → PyTorch → CNNs & RNNs.
PHASE 05
Transformers & LLMs
WEEKS 10–12
Attention from scratch. Build nanoGPT. Tokenization. Pre- and post-training.
PHASE 06
RAG Engineering
WEEKS 13–15
Chunking, embeddings, HNSW, hybrid search, reranking, HyDE, ColBERT.
PHASE 07
Eval & Production
WEEKS 16–17
Golden sets, RAGAS, LLM-as-judge, FastAPI, Redis, Langfuse, Docker.
PHASE 08
Agents & MCP
WEEKS 18–19
ReAct, tool use, MCP servers, CRAG, prompt injection defense.
PHASE 09
Fine-Tune & Research
WEEKS 20–22
LoRA, QLoRA, quantization, Ollama, vLLM. Reading papers on schedule.
PHASE 10
Capstone
WEEKS 23–24
Ship one thing so good it speaks for you at interviews.
NEXT
Get hired.
WEEK 25 →
AI Engineer. AI Product Engineer. ML Researcher. Portfolio does the talking.
02 / WHAT'S INSIDE

Four things. All free.

1
Sequenced curriculum
Every phase, every week. Every resource curated and linked — Karpathy videos, 3Blue1Brown, ISLP, the original papers. No filler.
2
Obsidian knowledge graph
175+ concept notes with wikilinks. Open in Obsidian (free), hit Cmd+G, and watch the entire field of AI engineering appear as an interactive graph.
3
Interactive progress tracker
A standalone HTML page (this site!) that persists your progress in localStorage. 210+ tasks, 11 phase progress bars. Nothing to install.
4
21 shipped projects
Every phase has builds. House-price predictor → MLP on MNIST → nanoGPT → production RAG → CRAG agent → LoRA fine-tune → capstone. Your portfolio emerges.

Most AI "bootcamps" teach you a framework in six weeks.

This roadmap teaches you the field in six months — from vectors to agents — with every hour of your time
pointing at the highest-leverage material on the internet.

03 / GOLDEN RULES

Four rules. Non-negotiable.

  1. Read the theory, implement it from scratch, use the library, ship a project — every topic.
  2. If you can't explain it, you don't understand it. Write a note.
  3. Papers before libraries. The arXiv link loads faster than the docs.
  4. One project per phase, minimum. Your GitHub is your résumé.
04 / KNOWLEDGE GRAPH

Every concept, connected.

The repo ships with a pre-built Obsidian vault — 175+ concept notes, all cross-linked with [[wikilinks]]. Open it in Obsidian and hit one keyboard shortcut to see the entire field of AI engineering as an interactive graph.

  1. 01
    Download Obsidian
    Free. macOS / Windows / Linux. obsidian.md ↗
  2. 02
    Open folder as vault
    Point it at obsidian-vault/ inside the cloned repo.
  3. 03
    Press ⌘+G (or Ctrl+G)
    Graph view opens. Every concept is a node. Every [[link]] is an edge. Click any node to jump to the note.
Get Obsidian ↗
Start today.
What else were you going to do?
Open the tracker →