What to Learn Next

You've covered the 13 basics. Now it's time to specialize. Three popular paths:

Path 1: Web Development

If you want to build websites and web apps:

  1. HTML & CSS — structure and styling. MDN is the gold standard reference.
  2. JavaScript in the browser — DOM manipulation, events, fetch API.
  3. One framework — React is the safest first choice; Vue and Svelte are gentler alternatives.
  4. A backend — Node.js, Python (Django/Flask), or Go. Pick based on what you want to build.
  5. Databases — start with SQL (PostgreSQL), then explore NoSQL if needed.

First project: a personal site or portfolio. Second: a CRUD app (something with a database).

Path 2: Data & Analytics

If you want to work with data, make charts, and eventually ML:

  1. Python deeply — comfort with lists, dicts, comprehensions.
  2. NumPy & pandas — the workhorses of data analysis.
  3. Matplotlib / Plotly — for visualization.
  4. SQL — non-negotiable in any data role.
  5. Statistics & ML — once you're comfortable, courses by Andrew Ng (free on Coursera).

First project: analyze a public dataset (Kaggle has thousands).

Path 3: Mobile

If you want apps in people's pockets:

  • iOS: Swift + SwiftUI. Native macOS development environment (Xcode).
  • Android: Kotlin + Jetpack Compose.
  • Cross-platform: React Native or Flutter (one codebase, both stores).

First project: a clone of a simple app you actually use (notes, weather, list).

Skills Useful in Any Path

  • Git & GitHub — start now, learn by using. git add ., commit, push, pull.
  • Command line basics — cd, ls, mv, rm, grep.
  • Reading documentation — practice with MDN or the Python standard library docs.
  • Asking good questions — Stack Overflow has a guide.
  • Testing — write small tests as you code; the time you save is enormous.

Free, High-Quality Follow-Ups

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The most important advice

Pick one path. Don't sample. Six months of focused work in one direction beats two years of jumping between three.