Learn from the best, everywhere.
Otomas is one part of the picture. Here's who and what we point our own students to when a lesson isn't enough.
Top instructors in AI
Andrej Karpathy
Founding Engineer, OpenAI · Ex-Tesla AI
Founding member of OpenAI and former Director of AI at Tesla. Famous for building neural networks from scratch on stream and making backprop click for millions through his 'Zero to Hero' series.
Andrew Ng
Co-Founder, Coursera & DeepLearning.AI
Founded Coursera and DeepLearning.AI, and formerly led Google Brain and Baidu's AI Group. His Stanford CS229 notes and Machine Learning course have quietly trained more engineers than any bootcamp.
Cynthia Rudin
Professor of Computer Science, Duke University
Leads Duke's Interpretable Machine Learning Lab and has spent her career arguing — and proving — that high-stakes models don't need to be black boxes to be accurate.
Channels worth subscribing to
The animated-explainer creators we'd point to even if we didn't make Otomas.
3Blue1Brown
8.4M subscribers
Grant Sanderson's animated math series — the reason half the internet finally understands linear algebra and calculus.
StatQuest with Josh Starmer
1.7M subscribers
Josh Starmer breaks down statistics and machine learning with the same three words — "Triple BAM!" — and somehow it always clicks.
Visually Explained
~180K subscribers
Dense math and ML topics — Kalman filters, attention, transformers — rebuilt frame-by-frame until the intuition is unavoidable.
Infinite Codes
~90K subscribers
Programming, data science, and AI explainers for people who'd rather build the thing than read another slide about it.
Core resources
Free, primary-source material worth bookmarking.
CS229 Lecture Notes
Andrew Ng's full Stanford machine learning notes — the same math behind the Coursera course, without the video.
DataCamp Cheat Sheets
Quick-reference sheets for Python, SQL, pandas, and statistics — for when you know the concept but forgot the syntax.
AI & Data Scientist Roadmap
A visual, step-by-step roadmap for going from zero to job-ready in AI and data science.
Worth reading
When you want the depth a video can't fit in ten minutes.
Machine Learning Yearning
Andrew Ng
A free, practical field guide to debugging and prioritizing ML projects — no math, just decisions.
The Hundred-Page Machine Learning Book
Andriy Burkov
Exactly what it sounds like: the entire field, distilled into a hundred dense, readable pages.
Deep Learning
Goodfellow, Bengio & Courville
The field's closest thing to a textbook bible — free to read online, chapter by chapter.