Course Content
Introduction to Reinforcement Learning
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Overview of Reinforcement Learning
Mathematical Foundations of RL
Multi-Armed Bandits and Fundamental RL Concepts
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Understanding Multi-Armed Bandit Problem
Markov Decision Process (MDP)
Dynamic Programming in RL
Model-Free RL: Monte Carlo & Temporal Difference Learning
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Monte Carlo Methods
Temporal Difference Learning (TD-Learning)
Deep Reinforcement Learning (Deep RL)
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Introduction to Deep RL
Deep Q-Networks (DQN)
Policy Gradient Methods
Advanced RL Algorithms
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Actor-Critic Methods
Evolutionary Strategies and Genetic Algorithms in RL
Model-Based RL
Applications of RL in Robotics and Games
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Applying RL in Robotics
RL for Game Playing
RL for Finance, Healthcare, and Real-World Applications
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RL in Finance
RL in Healthcare
Distributed RL and Multi-Agent Systems
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Distributed RL
Multi-Agent Reinforcement Learning (MARL)
RL Deployment, Performance Optimization, and Ethical Considerations
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Deploying RL Models
Performance Optimization in RL
Ethical Considerations in RL
Capstone Project and Certification Exam
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Capstone Project
Certification Exam
Certification Course in Reinforcement Learning
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