How This Course Works
One product, built piece by piece
You do not build fourteen small demos. You build one product, the BrightCart support assistant, and every module adds a part to it. By the end you have a deployed service you can show in an interview and explain line by line.
The product is described in 03-the-brightcart-project.md.
Pictures first
Every lesson is a walk through one example, one picture at a time. A figure shows an idea; a short paragraph says what the figure shows in plain words; a short block of code proves it; a walkthrough explains every line of that code. Then the next figure. A lesson has fifteen to thirty figures and takes thirty to forty-five minutes to read properly.
The same colours mean the same things in every figure:
| Colour | Means |
|---|---|
| Blue | Your system, the normal path |
| Amber | The model, anything uncertain |
| Green | Correct, safe, passed |
| Red | Failure, attack, danger |
| Grey | Optional, background, ignored |
The shape of every lesson
| Part | What happens | Why it is there |
|---|---|---|
| The situation | A problem at BrightCart | You learn the idea because you need it |
| A real case, first | Something that really happened, from a published source, cited | So you know the idea matters outside a course |
| The idea | Figures and short paragraphs, one running example throughout | The picture comes before the vocabulary and the formula |
| Run it | A short piece of code, pasted into Colab, with a code walkthrough | You see it work, and you understand every line |
| Break it | You make it fail on purpose | Real systems fail; see the failure here first |
| In production | What teams do with this at scale | The part most courses leave out |
| Check yourself | Three to five questions, answers hidden until you click | You find out whether it stuck |
| Exercise | One task with a way to check it | You do it, not just read it |
| Key terms and sources | A short glossary and the sources the lesson used | So you can go further |
Three depths of topic
Not every topic deserves the same attention. Each one is marked in its heading:
| Mark | Meaning | What you get |
|---|---|---|
| (Essential) | You cannot do the job without it | Figures, code and a "break it" step |
| (Recommended) | Skip it only if you have a reason | A figure and a short section, often with code |
| (Optional) | Knowing it exists is enough | An "awareness card": what it is, when you would need it |
If you are short of time, do the Essential sections of every module first and come back for the rest.
What every module contains
| File | What it is |
|---|---|
README.md | What the module is for, what you need to know first, the lesson list |
| Numbered lessons | One file per group of topics |
...-module-lab.md | A guided build that adds this module's piece to BrightCart |
...-incident-file.md | A real, published failure, then the same failure replayed on BrightCart and fixed |
How to run the code
All code runs in Google Colab. Open a new notebook, paste each code block into a cell in order, and run it. No installation is needed.
Every lesson that calls a model starts with the same short setup cell. It lets you choose between three model providers by changing one word. Groq and Gemini work in Colab with a free key. Ollama runs a model on your own computer, so if you choose it you work in a code editor on your machine. Setup for both routes, and how to run the whole project locally: 02-setup-colab-and-llm-providers.md.
The tools
Everything in the course is open source, apart from the hosted model services, which are shown as options. The course uses LangChain for calling models and LangGraph for multi-step workflows and agents. Where it helps you understand, a lesson first builds the mechanism by hand in plain Python, then shows the framework's version, so you know what the framework is doing for you.
Your answers will not match ours exactly
Language models do not return the same words every time. When a lesson shows output, yours may be worded differently. That is normal, and building reliable software on top of an unpredictable component is the main skill this course teaches. Every number printed in a lesson came from running that lesson's code on the date shown.