Global Certificate in Reinforcement Learning Strategies: Connected Systems

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The 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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By enrolling in this course, learners acquire essential skills in reinforcement learning, model-based and model-free methods, deep reinforcement learning, and multi-agent systems. These skills empower learners to create intelligent systems that can make decisions based on the environment, improving system performance, and efficiency. Furthermore, this program equips learners with the ability to apply these techniques in various connected systems, including IoT devices, autonomous vehicles, and smart grids, enhancing their career advancement opportunities.

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ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Introduction to Reinforcement Learning Strategies in Connected Systems
โ€ข Markov Decision Processes (MDPs) and Reinforcement Learning
โ€ข Q-Learning and Deep Q-Networks (DQNs) in Connected Systems
โ€ข Policy Gradients and Actor-Critic Methods in Reinforcement Learning
โ€ข Multi-Agent Reinforcement Learning for Connected Systems
โ€ข Deep Deterministic Policy Gradient (DDPG) for Continuous Control
โ€ข Proximal Policy Optimization (PPO) and Trust Region Policy Optimization (TRPO)
โ€ข Reinforcement Learning Applications in Connected Devices and Internet of Things (IoT)
โ€ข Ethics and Security Considerations in Reinforcement Learning for Connected Systems

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
GLOBAL CERTIFICATE IN REINFORCEMENT LEARNING STRATEGIES: CONNECTED SYSTEMS
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
UK School of Management (UKSM)
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05 May 2025
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