Reinforcement Learning (RL) is characterized by an agent continuously interacting and learning from a stochastic environment. Reinforcement Learning is a branch of Artificial Intelligence that formalizes this trial-and-error method of learning. RL is essentially the science of making sequential decisions. Reinforcement Learning is also a cross disciplinary subject that intersect with many disciplines of science such as optimal control, evolutionary learnings, dynamics programming etc.
The Reinforcement Learning - Essentials training course will teach you the fundamental concepts and techniques of various RL algorithms.
By attending Reinforcement Learning - Essentials workshop, delegates will learn to:
- Understand and apply the fundamental concepts of reinforcement learning
- Use RL on OpenAI Gym
- Build value-based reinforcement learning systems
- Build model-based reinforcement learning systems
- Build policy-based reinforcement learning systems
- Assess reinforcement learning systems and suggest more advanced reinforcement learning systems
- Robotics Engineers
- Machine Learning Developers
- AI Practitioners