What you’ll learn
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Define what is Reinforcement Learning?
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Apply all what is learned using state-of-the art libraries like OpenAI Gym, StabeBaselines, Keras-RL and TensorFlow Agents
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Define what are the applications domains and success stories of RL?
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Define what are the difference between Reinforcement and Supervised Learning?
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Define the main components of an RL problem setup?
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Define what are the main ingredients of an RL agent and their taxonomy?
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Define what is Markov Reward Process (MRP) and Markov Decision Process (MDP)?
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Define the solution space of RL using MDP framework
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Solve the RL problems using planning with Dynamic Programming algorithms, like Policy Evaluation, Policy Iteration and Value Iteration
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Solve RL problems using model free algorithms like Monte-Carlo, TD learning, Q-learning and SARSA
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Differentiate On-policy and Off-policy algorithms
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Master Deep Reinforcement Learning algorithms like Deep Q-Networks (DQN), and apply them to Large Scale RL
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Master Policy Gradients algorithms and Actor-Critic (AC, A2C, A3C)
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Master advanced DRL algorithms like DDPG, TRPO and PPO
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Define what is model-based RL, and differentiate it from planning, and what are their main algorithms and applications?
Can I download Reinforcement Learning course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Reinforcement Learning course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
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