State-of-the-art Research of Deep Reinforcement-learning

Course Overview

Skills and Knowledge:
By taking this course, students will acquire state-of-the-art research knowledge regarding OpenAI, DeepMind, Google, and Microsoft research in the field of Deep Reinforcement-learning. This includes advanced exploration methods, chatbot based Deep RL, evaluation strategies, advanced RL metrics, navigating robot getting human language instructions, merging on-policy and off-policy gradient estimation, hierarchical RL, and more advanced topics. Students will also be able to validate their knowledge by answering short quizzes of each lecture and complete the course in approximately two hours.
Professional Growth:
This course provides a comprehensive overview of the latest state-of-the-art research in Deep Reinforcement-learning. It covers topics such as advanced exploration methods, chatbot based Deep RL, evaluation strategies, advanced RL metrics, navigating robot getting human language instructions, merging on-policy and off-policy gradient estimation, hierarchical RL, and more. Through this course, professionals can gain a better understanding of the latest research in Deep Reinforcement-learning, validate their knowledge by answering short quizzes of each lecture, and be able to complete the course in approximately two hours. This course is a great opportunity for professionals to stay up-to-date with the latest research in Deep Reinforcement-learning and to further their professional growth.
Further Education:
This course appears to be suitable for preparing further education in the field of Deep Reinforcement-learning. It covers the latest state-of-the-art research knowledge from OpenAI, DeepMind, Google, and Microsoft, and provides quizzes to validate the knowledge. Additionally, the course is estimated to take only ~2 hours to complete, making it an efficient way to gain knowledge in the field.