Start Here¶
One page to route every learner. Pick your background, follow the sequential path in the Learn tab, and build something real.
How the site works
Open Learn in the top nav — 16 courses in order (01–16). Each course page lists its lessons. No module codes in the UI.
Quick setup
Need install commands only? See Getting Started.
Who are you?¶
| Persona | Background | Start with | Time to first app |
|---|---|---|---|
| Complete beginner | No CS / no Python | Prerequisites → 01 GenAI Foundations → 02 AI Essentials | ~2 weeks part-time |
| Software engineer, new to AI | Can code, never built with LLMs | 02 AI Engineering Essentials | ~3 days |
| ML engineer → LLM/agents | Knows training, needs product stack | 05 Large Language Models or 06 RAG | ~1 week |
| Career switcher | Changing into AI engineering | Learn overview + Build These First | 4–6 months part-time |
Need a week-by-week schedule? See Study Plans.
I want to learn…¶
By goal¶
| I want to… | Read first | Then | Build |
|---|---|---|---|
| Understand how LLMs work | 01 → 04 Transformers → 05 LLMs | Deep Dives | Course 04 exercises |
| Call LLM APIs in production | 02 AI Essentials | 12 LLMOps | Project 1: Doc Q&A bot |
| Build RAG over my documents | 06 RAG | 10 Vector DBs | Project 2: Enterprise RAG |
| Build AI agents | Agent Engineering track or 07 AI Agents | 08 Agent Harness | Project 4: Tool-using agent |
| Ship multi-agent systems | 09 Multi-Agent Systems | 13 LLM Evals | Project 5: Multi-agent research |
| Fine-tune a model | 15 Fine-Tuning | 05 LLMs — fine-tuning lessons | Project 8: Domain fine-tune |
| Evaluate & monitor LLM apps | 13 LLM Evaluation | Evals hub | Project 9: Eval suite |
| Use Claude Code / agentic IDE skills | Modern AI (2026) | Skills & Rules | Custom skill for your repo |
| Get a job in AI engineering | This page → Learn | Build These First (portfolio) | 3 projects + 16 Capstones |
By concept¶
| Concept | Primary course | Hub / deep dive |
|---|---|---|
| Transformers | 04 Transformers & Attention | Attention math |
| Prompting | 11 Prompt Engineering | AI Essentials · Prompts |
| RAG | 06 RAG | Graph RAG |
| Agents | 07 AI Agents | Agentic AI hub |
| MCP & tools | 08 Agent Harness | Agent Engineering · Tools |
| Safety | 14 AI Safety | Prompt injection |
Full index: Topic Map · Glossary
Prerequisite chains¶
Expand prerequisite diagram and course requirements
Follow these before jumping ahead. Skipping steps causes confusion later.
flowchart TB
subgraph Beginner["Complete beginner"]
P[Prerequisites]
C01[01 GenAI Foundations]
C02[02 AI Essentials]
P --> C01 --> C02
end
subgraph SWE["Software engineer"]
C02b[02 AI Essentials]
C06[06 RAG]
C07[07 AI Agents]
C02b --> C06 --> C07
end
subgraph ML["ML engineer"]
C05[05 LLMs]
C06b[06 RAG]
C15[15 Fine-Tuning]
C05 --> C06b
C05 --> C15
end
C02 --> C06
C06 --> C07
C07 --> C08[08 Harness]
C08 --> C09[09 Multi-Agent]
C07 --> C13[13 Evals]
C06 --> C12[12 LLMOps]| Course | Requires | Self-check |
|---|---|---|
| 01 GenAI Foundations | Python basics, comfort with fractions/exponents | Can you run pip install numpy and write a function? |
| 02 AI Essentials | Course 01 or equivalent SWE experience | Can you call a REST API in Python? |
| 03–04 Neural nets & transformers | Course 01 math lessons, NumPy | Can you explain matrix multiply and softmax? |
| 05 LLMs | Course 04 or transformer lessons in course 01 | Can you draw the transformer block? |
| 06 RAG | Course 02 (APIs) + basic embeddings concept | Can you chunk text and call an embedding API? |
| 07 AI Agents | Course 02 + course 06 recommended | Can you explain retrieve-then-generate? |
| 08 Agent Harness | Course 07 agent loop | Can you implement a ReAct loop? |
| 09 Multi-Agent | Courses 07 + 08 | Can you trace a multi-step agent run? |
| 15 Fine-Tuning | Course 05 fine-tuning basics | Do you know LoRA vs full fine-tune? |
| 16 Capstones | Courses 06 + 07 minimum | Have you built one RAG app and one agent? |
Your first 4 weeks (career switcher roadmap)¶
Expand 4-week career switcher plan
| Week | Focus | Courses | Milestone |
|---|---|---|---|
| 1 | Python + first API call | 01 (prerequisites), 02 | Working chat script + token cost log |
| 2 | Prompts + RAG basics | 02 exercises, 06 lessons 1–5 | Doc Q&A over 10 PDFs |
| 3 | Agents + harness | 07 lessons 1–7, 08 lessons 1–3 | Agent with 2 tools |
| 4 | Evals + portfolio polish | 13 lessons 1–3, Build These | One project on GitHub with README |
After week 4: continue the Learn path through production (12–14) and advanced (15–16).
Practice: exercises & projects¶
| Resource | What it is | Link |
|---|---|---|
| Exercises | Starter/solution .py files per course |
Exercise index |
| Build These First | 10 portfolio projects mapped to courses | build-these.md |
| Capstones | Full production briefs (course 16) | Capstone projects |
When to use RAG vs fine-tune vs agents¶
Quick decision guide — full tables in FAQ.
| Need | Use | Avoid |
|---|---|---|
| Answer from your documents | RAG | Fine-tuning for facts |
| Consistent format/style every time | Fine-tune or strict prompts | Hoping RAG fixes tone |
| Multi-step tasks with tools | Agent | Long deterministic workflow pretending to be an agent |
| Deterministic pipeline (ETL, approvals) | Workflow | Autonomous agent |
| Cheapest first attempt | Prompt engineering | Fine-tune on day one |
Stuck? Read this¶
| Problem | Go to |
|---|---|
| Don't know where to start | This page — pick a persona above |
| Lesson assumes math I don't have | 01 · Math foundations |
| API key / rate limit errors | FAQ — Troubleshooting |
| Term I don't understand | Glossary |
| Want a portfolio project | Build These First |
| Content gap or bug | Contribute · GitHub Issues |
Site map¶
| Tab / page | Purpose |
|---|---|
| Start Here (this page) | Persona routing, prerequisites, goals |
| Learn | Sequential courses 01–16 + optional tracks |
| Study Plans | Week-by-week schedules by persona |
| Topic Map | Concept → course lookup |
| Reference | FAQ, glossary, deep dives, resources |
| Projects | Portfolio builds |