Physical Intelligence's co-founder put his entire Berkeley course on YouTube: every lecture from this spring, plus the homework code. "CS 185/285: Deep Reinforcement Learning," Sergey Levine (@svlevine), UC Berkeley, Spring 2026. Imitation learning, policy gradients, actor-critic, Q-learning, model-based RL, offline RL, exploration, RL for LLMs and multi-task learning - 25 lectures plus 2 guest talks, about 36 hours, free. Lectures 2 and 3 are learning from human demos, the same idea behind ALOHA and π0. the rest is how a robot keeps getting better after the demos run out. Figure is hiring an RL Engineer for whole-body control right now, at $150K–$350K. this course is what the "RL" in that title means. Lectures: Homework: P.S. lecture 14 is RL with sequences and LLMs, the same toolkit used to train today's reasoning models.