GitHub Course Offers Hands-On Curriculum for Modern Reinforcement Learning
A new open-source course on GitHub, titled 'Hands-On Modern RL', provides a comprehensive curriculum for learning reinforcement learning (RL) through practical application. The course is designed for learners transitioning from supervised learning to RL, researchers, and practitioners interested in advanced topics like LLM alignment and RLVR. It emphasizes a practice-first approach, starting with runnable code and observable training behavior before delving into theoretical concepts. The course covers a wide range of topics, from classical RL fundamentals to advanced methods like policy gradients, PPO, and multi-agent systems. It also includes modules on LLM post-training, preference alignment, and multimodal reinforcement learning. 
