A 25-year-old MIT PhD student stood in front of a classroom in January 2018 and started teaching the most ambitious deep learning course on the planet. His name is Alexander Amini. He's been teaching it every single January for the last 8 years, and the entire course is uploaded to YouTube for free within weeks of being recorded on campus. Here's what almost nobody tells you about this course. MIT 6.S191 was never designed to be a watered down public version of an internal class. It is the internal class. The same lectures the on-campus students sit through are the lectures uploaded to YouTube. The same labs the on-campus students submit are the labs you can run in Google Colab from your laptop. The same problem sets. The same projects. The same guest lectures from researchers at OpenAI, Google DeepMind, and NVIDIA. The only thing you don't get is the MIT credential. Everything else is identical. Amini and his co-instructor Ava Soleimany rebuild the course every single year because the field moves so fast that last year's lectures are already half obsolete. The 2026 version covers the architecture of frontier LLMs, modern RLHF, multimodal models, and diffusion in a way that did not exist in any curriculum even 18 months ago. A self-taught engineer in Lagos, a high schooler in Karachi, and a working software developer in Berlin can all open the same playlist tonight and be learning from the same instructors as a 22-year-old paying $60,000 a year to sit in a Cambridge auditorium. This is the most quietly democratizing thing happening in technical education and almost nobody outside the field has heard of it. The course is at introtodeeplearning.com. The lectures are on YouTube. Both are free. Most people will scroll past this post. The few who open the link will be in a different position by March than they are tonight.