All you need is one link to become a pro in some area. Here is a list of all the best resources (you might not find elsewhere?) to help you get started in mastering a subject. Enjoy! Also, let me know if you are interested in contributing to the list.
The first 20 hours: https://www.youtube.com/watch?v=5MgBikgcWnY
- JavaScript: http://speakingjs.com/es5/index.html
- ES6 (after you understand the fundamental JS materials): https://ponyfoo.com/articles/es6
- JS Style: https://github.com/airbnb/javascript
- JS Pattern: https://addyosmani.com/resources/essentialjsdesignpatterns/book/
- Front-end development
- ReactJS: http://courses.reactjsprogram.com/courses/reactjsfundamentals
- Redux (after knowing ReactJS): https://learnredux.com
- React Native: https://facebook.github.io/react-native/docs/tutorial.html
- AngularJS: https://toddmotto.com/ultimate-guide-to-learning-angular-js-in-one-day/
- NodeJS: https://www.codeschool.com/courses/real-time-web-with-node-js
- jQuery: http://jqfundamentals.com
- HTML & CSS (related to JS): http://learn.shayhowe.com/html-css/
- Ruby on Rails: https://www.railstutorial.org/book
- Python Flask: http://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world
- Scala: http://twitter.github.io/scala_school/
- Go: https://astaxie.gitbooks.io/build-web-application-with-golang/content/en/preface.html
- Rust: https://doc.rust-lang.org/book/
- Lua: http://nova-fusion.com/2012/08/27/lua-for-programmers-part-1/
- Kotlin: http://kotlinlang.org/docs/reference/
- PHP: http://www.phptherightway.com/
- Interview: https://leetcode.com
- ICPC: http://www.stanford.edu/class/cs97si/
- C++ STL
- Git: http://marc.helbling.fr/2014/09/practical-git-introduction
- Text Editor: http://www.learnenough.com/text-editor-tutorial
- Markdown: https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet
- LaTex: http://www.latex-tutorial.com/tutorials/
- Vimscript: http://learnvimscriptthehardway.stevelosh.com/
- Hacking: https://www.hacksplaining.com
- Design: https://medium.com/hh-design/design-resources-5071be5f2e43
- Machine Learning: https://www.coursera.org/learn/machine-learning
- Neural Networks: http://neuralnetworksanddeeplearning.com/index.html
- Deep Learning: http://www.deeplearningbook.org/
- Game Programming: http://www-cs-students.stanford.edu/~amitp/gameprog.html
- Cryptography: https://www.crypto101.io
- Networking: http://beej.us/guide/bgnet/output/html/multipage/index.html
- Data Mining: http://guidetodatamining.com/
If you would like to contribute to this list you can reach out to me via email, twitter, or fork this repository and make a pull request.
- Email: vic.yeh at ucla dot edu
- Twitter: @vicohyeh