Masterclass Certificate in RL Problem Solving Strategies
-- ViewingNowThe Masterclass Certificate in Reinforcement Learning (RL) Problem Solving Strategies is a comprehensive course designed to equip learners with essential skills in RL, a critical area of artificial intelligence. This course is vital in today's data-driven world, where businesses are seeking professionals who can leverage RL to make informed, strategic decisions.
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• Foundations of Reinforcement Learning: Introduction to RL, Markov Decision Processes (MDPs), value functions, policy gradients
• Deep Reinforcement Learning: Deep Q-Networks (DQNs), policy gradients with function approximation, actor-critic methods
• Exploration and Exploitation Strategies: Epsilon-greedy, Boltzmann exploration, entropy-based methods, UCB
• Monte Carlo Tree Search: MCTS algorithms, Upper Confidence Bounds for Trees (UCT), applications in games and planning
• Multi-Agent Reinforcement Learning: Decentralized RL, independent Q-learning, collaboration and competition, game theory
• Transfer Learning in RL: Knowledge transfer between tasks, meta-learning, multi-task RL
• Safe and Efficient RL: Constrained RL, risk-sensitive RL, sample-efficient methods, Bayesian RL
• Advanced Topics in RL: Hierarchical RL, inverse RL, continuous state and action spaces, intrinsic motivation
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- ThreeFourHoursPerWeek
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