Learn at 1337 Foundation
A practical coding course for beginners. Spend two weeks trying HTML, CSS, and Python, then follow the path that feels right: building for the web or working with data and AI.
Self-paced · No coding experience needed · Learn by building
01 / A two-week sampler
Give each topic a few focused sessions. Take an evening or take longer; move on when you can use the idea in a small project and describe what it does.
Learn the shape of a web page: headings, links, images, lists, and meaningful sections. Keep your first version in Git and push it to GitHub. Spend one short session trying Python values and print, too.
Build
A one-page introduction to something you care about.
Use CSS to control color, type, spacing, and responsive layout. Alongside that, try Python values, conditions, loops, and a small function.
Build
A finished page and a tiny Python program. Notice which kind of problem you want to solve next.
02 / Pick your path
If you like shaping what people see and click, keep going with web development. If you like finding patterns, automating tasks, or building bots and AI tools, continue with Python. Both paths start with the same two-week sampler.
03 / The curriculum
Weeks 1–2 are shared. Choose one of the six-week continuations after the sampler. This is a suggested pace, not a deadline.
Weeks 03–08
Learn Values, variables, functions, arrays, objects, browser events, and the DOM.
Build Add real interactions to your page and explain what changes when someone clicks.
Learn HTTP, GET and POST, JSON, fetch, async work, loading states, and useful errors.
Build Request data, inspect the response, and open your first GitHub pull request.
Learn Components, props, state, lists, forms, and how updates flow through a page.
Build Turn the data view into reusable pieces that update when the data changes.
Learn Routes, server and client code, TypeScript basics, environment variables, and API routes.
Build Put private API keys on the server and keep the browser limited to public data.
Learn Choose and document a sports data source; account for empty, slow, or failed responses.
Build Show last night’s NBA games in three columns: away team, home team, and score.
Learn Responsive layout, accessibility basics, a useful README, and a final review.
Build Publish the scoreboard, link the data source, and walk someone through how it works.
Weeks 03–08
Learn Functions, lists, dictionaries, loops, and reading error messages.
Build Write a small command-line program that turns a question into a result.
Learn Read and write CSV and JSON, make requests, and handle missing data.
Build Create a score summary from a documented sports data source.
Learn Clean a dataset, ask a clear question, and use pandas to inspect the answer.
Build Share a short analysis with a chart and notes about where the data came from.
Learn Call a model through an API, keep credentials private, and check its output.
Build Make a small helper that answers from the data you collected.
Learn Break a task into steps, validate inputs, and keep actions narrow and reviewable.
Build Let the helper look up a score or summarize a dataset, then check the result.
Learn Organize files, document setup, handle errors, and show the work clearly.
Build Publish your data tool or assistant with a README and a short demo.
The weekly loop
Keep these open
Give both a quick first pass—an evening is plenty. Come back while you build until the ideas make sense in practice.