Reinforcement learning now has a dedicated course in the OMSCS program, and practitioner Eugene Yan has published an evaluation of it. The write-up, based on personal experience, focuses on CS7642 and the kind of work students actually do in it. The standout element is a project in which students land rockets using deep Q-learning, along with its variants.
The review frames the course as a hands-on introduction to deep RL rather than just a set of theory lectures. By presenting the rocket-landing task as "fun," Yan suggests the practical exercises are engaging while still pushing students through the core algorithms. The post also includes tips aimed at future students, though the exact advice is not detailed in the excerpt.
Because the article is a single source—a personal review rather than a comparative study—there is no external evidence to weigh against its claims. Readers should treat the experience as one practitioner's viewpoint on the course's workload and value.