Global Certificate in Reinforcement Learning Strategies: Connected Systems
-- ViewingNowThe Global Certificate in Reinforcement Learning Strategies: Connected Systems course is a comprehensive program that emphasizes the application of reinforcement learning techniques in designing and optimizing connected systems. This course gains significance with the increasing industry adoption of AI and machine learning technologies, creating a high demand for skilled professionals in reinforcement learning strategies.
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⢠Introduction to Reinforcement Learning Strategies in Connected Systems
⢠Markov Decision Processes (MDPs) and Reinforcement Learning
⢠Q-Learning and Deep Q-Networks (DQNs) in Connected Systems
⢠Policy Gradients and Actor-Critic Methods in Reinforcement Learning
⢠Multi-Agent Reinforcement Learning for Connected Systems
⢠Deep Deterministic Policy Gradient (DDPG) for Continuous Control
⢠Proximal Policy Optimization (PPO) and Trust Region Policy Optimization (TRPO)
⢠Reinforcement Learning Applications in Connected Devices and Internet of Things (IoT)
⢠Ethics and Security Considerations in Reinforcement Learning for Connected Systems
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