Certificate in Reinforcement Learning Strategies: Connected Systems
-- ViewingNowThe Certificate in Reinforcement Learning Strategies: Connected Systems course is a valuable asset for professionals seeking to enhance their expertise in artificial intelligence. This program focuses on reinforcement learning, a powerful machine learning approach that enables agents to learn from their interactions with an environment and make informed decisions.
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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) and Proximal Policy Optimization (PPO)
• Reinforcement Learning Applications in Connected Transportation Systems
• Reinforcement Learning Applications in IoT and Edge Computing
• Designing and Optimizing Reinforcement Learning Algorithms for Connected Systems
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
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- ThreeFourHoursPerWeek
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