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Updated in [August 18th, 2023]

Skills and Knowledge:
The DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning [1&13] provides an introduction to reinforcement learning and its relation to AI. Through this course, participants will acquire knowledge and skills in the areas of reinforcement learning, AI, and machine learning. Specifically, participants will learn about the fundamentals of reinforcement learning, including Markov Decision Processes, Bellman equations, and temporal difference learning. They will also gain an understanding of the different types of reinforcement learning algorithms, such as Q-learning, SARSA, and policy gradient methods. Additionally, participants will gain an understanding of the applications of reinforcement learning, such as robotics, autonomous driving, and game playing. Finally, participants will gain an understanding of the challenges and opportunities of reinforcement learning, such as exploration-exploitation trade-offs and deep reinforcement learning.
Professional Growth:
The DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning provides an in-depth look into the field of reinforcement learning and its applications in artificial intelligence. Through this course, professionals can gain a better understanding of the fundamentals of reinforcement learning, as well as its potential applications in AI. The course also provides an opportunity to learn from experts in the field, such as Research Scientist Hado van Hasselt, who introduces the course and explains how reinforcement learning relates to AI. By taking this course, professionals can gain a better understanding of the concepts and techniques of reinforcement learning, which can help them to further their professional growth.
Further Education:
The DeepMind x UCL RL Lecture Series - Introduction to Reinforcement Learning provides an in-depth introduction to reinforcement learning and its applications in artificial intelligence. The lecture series is presented by Research Scientist Hado van Hasselt and covers topics such as Markov Decision Processes, Monte Carlo methods, and Temporal Difference Learning. The lecture series is suitable for those looking to prepare for further education in reinforcement learning and artificial intelligence.