Learn Python the way you will use it.
Short, focused lessons that take you from your first print() to writing real scripts: reading data, automating everyday tasks, and building small tools you will use again. Runs in your browser. Works on a phone. Free forever.
Not sure which path? The roadmap puts them in order, from zero to employable.
Printable cheat sheets
24 topics, one A4 page each, from strings and loops to NumPy and pandas. Every example on them is run with Python before the sheet is printed, and each sheet ends with the mistakes people often make.
See all 24 cheat sheets
strings
lists
dictionaries
f-stringsChoose your path
222 lessons · 53h 17m totalCore Python
4 pathsTake these in order, from your first print() to large projects.
Python Fundamentals
Start here if you've never written code. Variables, control flow, functions, lists and dictionaries: the basics you need before anything else makes sense.
- level
- beginner
- requires
- no prior coding
- length
- 19 lessons · 4h 33m
- format
- read → run → quiz
Python Intermediate
After the basics, this is where Python becomes useful for real work: OOP, files, exceptions, comprehensions, decorators and the other techniques you will use every day.
- level
- intermediate
- requires
- Fundamentals or equivalent
- length
- 13 lessons · 3h 52m
- format
- read → run → quiz
Python Advanced
Metaclasses, descriptors, async, type hints and performance: the topics you need to understand how large Python projects and libraries work.
- level
- advanced
- requires
- Intermediate
- length
- 9 lessons · 3h
- format
- deep dives
Projects
Use what you have learned to build complete, working Python programs. Each project goes through the build step by step, then gives you extra goals to try on your own.
- level
- beginner
- requires
- Comfortable with Fundamentals
- length
- 15 lessons · 6h 30m
- format
- guided build
Choose a direction
After the basics, pick the area you want to work in.
Data science & AI
6 pathsFrom your first DataFrame to models and LLMs. Beginner on the first row, then deeper.
Data Science Fundamentals
An easy start in data science: what it is, why it matters, and your first hands-on pandas analysis. Each idea is explained in plain words before any technical terms.
- level
- beginner
- requires
- Fundamentals
- length
- 6 lessons · 1h 46m
- format
- guided
Machine Learning Fundamentals
Machine learning without heavy maths. Linear regression, classification, decision trees, and the metrics that tell you if a model is good.
- level
- beginner
- requires
- Fundamentals
- length
- 6 lessons · 1h 25m
- format
- guided
Deep Learning Fundamentals
Neural networks explained in plain words first, then built with Keras. CNNs for images, RNNs for sequences, and what each line of training code does.
- level
- beginner
- requires
- ML Fundamentals
- length
- 7 lessons · 2h 42m
- format
- guided
Data Science & ML
NumPy, Pandas, Matplotlib, and just enough statistics to not embarrass yourself. Real datasets, real questions, no toy examples.
- level
- intermediate
- requires
- Fundamentals
- length
- 9 lessons · 3h 15m
- format
- applied
Generative AI & LLMs
How ChatGPT, Claude and other large language models work (tokens, attention, embeddings, RAG, fine-tuning), and how to use them from Python.
- level
- intermediate
- requires
- Deep Learning Fundamentals
- length
- 6 lessons · 2h 12m
- format
- applied
AI & Deep Learning
Neural networks, CNNs, NLP, GANs, and how the parts of a production AI system fit together. Theory only where it helps, and working code everywhere else.
- level
- advanced
- requires
- Data Science
- length
- 9 lessons · 4h 11m
- format
- applied + project
Web & backend
4 pathsBuild web apps and APIs, secure them, store their data and put them online.
Web Frameworks
Flask, FastAPI and Django: when to use each one, how to build a working app in each, and the patterns real teams use. Authentication and databases have their own tracks.
- level
- intermediate
- requires
- Fundamentals + a touch of Intermediate
- length
- 12 lessons · 4h 38m
- format
- guided build
Auth & Security
Password hashing, sessions, JWT, OAuth2 with real providers, and the OWASP-flavoured security checklist every web app needs before it goes live.
- level
- intermediate
- requires
- Web Frameworks (or general HTTP literacy)
- length
- 4 lessons · 1h 31m
- format
- guided build
DevOps & Deploy
Docker, GitHub Actions, environments and secrets: the work that takes code from 'works on my laptop' to 'works in production'.
- level
- intermediate
- requires
- Intermediate Python + comfort with the command line
- length
- 4 lessons · 1h 34m
- format
- guided
Databases (Production)
The next step after SQLite: Postgres with psycopg/asyncpg, Redis for caching and queues, MongoDB for document data, and ORM patterns that stay fast in production.
- level
- advanced
- requires
- Intermediate (fileio, exceptions) and How-to databases
- length
- 4 lessons · 1h 49m
- format
- guided
Use any time
Open these whenever you need them: a task to solve, an error, a syntax reminder, a ready program, a habit to learn.
Python How-To
Step-by-step answers to the tasks people search for most: the terminal, Git, scraping, APIs, CSVs, databases, automation, testing, logging and packaging.
- level
- beginner
- requires
- any level: pick what you need
- length
- 14 lessons · 4h 44m
- format
- practical reference
Errors
The Python errors you are most likely to meet, from a wrong indent to a server that stops at 2am. For each one: what the message means, the code that causes it, and the fix. You can run every example here.
- level
- reference
- requires
- any level: bring your error message
- length
- 60 lessons · 3h 14m
- format
- look it up → fix it
Reference
Cheat sheets and a glossary for when you forget the syntax: comprehensions, slicing, f-strings, datetime, regex. Short pages with just the answer.
- level
- reference
- requires
- any level: when you need a fast answer
- length
- 25 lessons · 2h 21m
- format
- reference
Tips & tricks
Short, practical habits that experienced Python developers rely on: the before, the after, why it works, and when not to use it. Plus how real projects like Dropbox and Spotify used these ideas at scale.
- level
- any
- requires
- any level: start anywhere
- length
- 31 tips · 5 case studies
- format
- before → after, runnable
Short answers
One page per question people type into a search box: read a CSV, parse JSON, use SQLite, sort a dictionary by value, call an API. The code first, then the one or two things that trip people up.
- level
- any
- requires
- nothing: look up what you need
- length
- 26 questions
- format
- answer first, runnable
Python programs
Classic programs in order, from Hello World and leap years to sorting, file handling and small tools. Each page has the code, the real output, a Run button and a short explanation of how it works.
- level
- beginner first, then harder
- requires
- nothing: start at program 1
- length
- 195 programs · 141 for beginners
- format
- code, output, how it works
Lessons from incidents
Real outages, lost data and a malicious package (Cloudflare, GitLab, PyPI): what went wrong, told from each company’s own write-up, and the habit that would have caught it. Every story ends in code you can run.
- level
- intermediate
- requires
- basic Python
- length
- 3 incidents
- format
- story → cause → runnable fix
Tools that come with it
for the data science, ML and AI tracksThe data tracks expect you to run the code yourself, and you can. scikit-learn, XGBoost, LightGBM, pandas and statsmodels all run in this tab, with no install, and your code never leaves your device. Train a model, score it on a test split, plot the result. PyTorch and TensorFlow are the honest exceptions: no WebAssembly build exists, so those lessons ask you to run locally and say so plainly.
Notebook
Cells that share one Python session. Load a DataFrame in the first cell and every cell below can use it. You don't need to run the whole file again to change one line. Tables and plots render where you make them, and it autosaves.
Open the notebook →Practice datasets
Seven CSV files with real patterns in them, so a model you train can find something: housing, weather, retail, films, students and churn, plus one file that is messy on purpose, so you can practise cleaning data. One line to load any of them.
Browse the datasets →Playground
The full editor when you want a scratchpad rather than a notebook: multi-tab, syntax checking, package installs, and your session restored exactly where you left it.
Open the playground →Charts render as high-resolution images, and Plotly figures render live: you can drag to rotate a 3D scatter plot or a loss surface and look at it from every side.
Before you start.
A short, honest note. It takes two minutes to read.
What you'll get
- A working understanding of Python in roughly twelve hours of focused time.
- Real, useful scripts before the end of the second path.
- Lessons that run on any device you have: a phone, a school laptop, anything.
- Free, forever. Your code stays in the browser.
What we won't pretend
- This won't make you a senior engineer. Real depth comes from building your own things.
- It won't replace a CS degree if a job filter demands one.
- We don't cover every library, only the ones you are most likely to need.
- The hard parts are still hard. We explain them clearly, but we don't pretend they are easy.
Recently shipped
and what should come next is up to you222 lessons (including 60 error write-ups), 195 Python programs, 31 tips, 26 short answers and 24 cheat sheets so far, and the site is still being written. These four arrived most recently. We also ran every code example in the lessons again, fixed the ones whose output did not match the page, and rewrote the text in plainer English. There’s no newsletter and no notify me box. If there’s something you want next, say so with the feedback button. Requests are how we pick what to build.
input() works in every browser
Programs that ask a question with input() or pause with time.sleep() now work in Safari, Firefox and every browser on iPhone and iPad, in the editor and in the lessons, and Stop works there too. The editor also completes names from your own code, for example math.sqrt after import math.
Choose your Python version
The editor now runs Python 3.14, 3.13, 3.12 or 3.11: click the status line above the output to switch, and share links keep the version. The lessons, examples and notebook stay on 3.13, the version every output on them was checked on.
See what changed →Python programs for beginners
195 classic programs, from adding two numbers to sorting, games and small tools. Each page has the code, the output and a short explanation, and you can run it in your browser.
Browse the programs →An error finder
Paste a traceback and it finds the page that fixes it (60 errors written up), or explains the error and points at the line of your code to look at. Failed runs in the editor and the lessons now have an Explain this error link.
Paste an error →Everything already here stays free, and everything new will be free too: no account, no paywall, no email sign-up.
No paywall, no premium tier, no email gate. Your code runs in your browser, not on servers we rent, which is what makes free possible. There are no ads today. When they arrive they'll be clearly labelled, and the lessons stay free either way.