This course will cover a wide variety of topics in embodied intelligence, including but not limited to control, reinforcement learning, self-supervised and unsupervised action, visual learning for robotics, generalization and meta-learning. The course will provide an overview of relevant topics and open questions in the area. There will be a strong emphasis on bridging the gap between many different fields of AI. The goal is for students to get both the high-level understanding of important problems and possible solutions, as well as low level understanding of technical solutions. We hope that this course will inspire you to approach problems in embodied learning from different perspectives in your research.