Global Certificate in Reinforcement Analysis Essentials
-- ViewingNowThe Global Certificate in Reinforcement Analysis Essentials is a comprehensive course designed to empower learners with the essential skills required in reinforcement analysis. This course is vital in today's data-driven world, where businesses are constantly seeking professionals who can analyze data and make informed decisions.
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Here are the essential units for Global Certificate in Reinforcement Analysis Essentials:
• Introduction to Reinforcement Learning: definitions, history, and applications.
• Markov Decision Processes (MDPs): finite and infinite horizon, discounted and undiscounted, stationary and non-stationary.
• Dynamic Programming: value and policy iteration, Bellman optimality equation.
• Monte Carlo Methods: simulation-based methods, first-visit and every-visit MC methods, on-policy and off-policy methods.
• Temporal Difference (TD) Learning: TD(0), TD lambda, SARSA, Q-learning.
• Function Approximation: linear, non-linear, and neural network-based methods.
• Deep Reinforcement Learning: Deep Q-Networks, Double Deep Q-Networks, Dueling Deep Q-Networks.
• Reinforcement Learning Applications: game playing, robotics, natural language processing, finance, and healthcare.
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