For all the self-taught geeks out there, here our content library with most of the learning materials we have produces throughout the years.
It makes sense to start learning by reading and watching videos about fundamentals and how things work.
Machine Learning Engineering (16 weeks)
Full-Stack Software Developer
Search from all Lessons
Curated list of small interactive and incremental exercises you can take to get better at any coding skill.
Curated section of projects to build while learning with simple instructions, videos, solutions and more.
Guides on different topics related to the technologies that we teach in our courses
Social & live learning
The most efficient way to learn: Join a cohort with classmates just like you, live streams, impromptu coding sessions, live tutorials with real experts, and stay motivated.
Enter your information and receive instant access
After you finished the begginers, functions and loops series; This series will really prepare you for your next job or any any other programming challenge. Practice everything there you need to know to build algorithms with python, from intermadiate to hard challenges: The entire tutorial is 👆 interactive, ✅ auto-graded and with. 📹 video tutorials.
Note: The exercises have automatic grading but its very rigid and string, my recomendation is to ignore the tests and use them only as a recomendation or you can get frustrated.
Each exercise is a small react application containing the following files:
Thanks goes to these wonderful people (emoji key):
Alejandro Sanchez (alesanchezr), contribution: (coder) 💻 (idea) 🤔, (build-tests) ⚠️ , (pull-request-review) 👀 (build-tutorial) ✅ (documentation) 📖
Paolo (plucodev), contribution: (bug reports) 🐛, contribution: (coder), (translation) 🌎
Marco Gómez (marcogonzalo), contribution: (bug reports) :🐛, (translation) 🌎
This project follows theall-contributors specification.Contributions of any kind are welcome!