Resource Library
A curated hub aggregating courses, certifications, 36+ tools, open-source projects, papers, media, news and communities to accelerate your AI career.
Good AI learning resources are abundant; finding them is the problem. This library curates the ecosystem across 8 tabs: courses and books with ratings and prices, certifications with industry-recognition notes, a tools ecosystem spanning LLM APIs to vector databases, and open-source projects worth studying with the specific lessons each teaches.
Beyond study material, the library covers how to stay plugged in: foundational and recent papers with why-read notes, podcasts and YouTube series, news sites, company and personal blogs, newsletters, machine learning communities by platform and activity level, conferences and who to follow. Pair it with the learning path to slot resources into a sequence.
Explore: Best ML courses & resources · Learning path planner · Mentors & bootcamps
Courses(5)
Machine Learning Specialization ↗
★ 4.9Coursera · Andrew Ng
Deep Learning Specialization ↗
★ 4.9Coursera · Andrew Ng
CS50's Introduction to AI with Python ↗
★ 4.8Harvard / edX · David J. Malan
Practical Deep Learning for Coders ↗
★ 4.8fast.ai · Jeremy Howard
Full Stack LLM Bootcamp ↗
★ 4.7The Full Stack · Industry Experts
Books(4)
Deep Learning ↗
Ian Goodfellow, Yoshua Bengio, Aaron Courville
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow ↗
Aurélien Géron
Pattern Recognition and Machine Learning
Christopher Bishop
The Hundred-Page Machine Learning Book ↗
Andriy Burkov