Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. In this instructor-led, live training in Mumbai (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems.
Part lecture, part discussion, exercises and heavy hands-on practice Apply advanced Reinforcement Learning algorithms to solve real-world problems Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.īy the end of this training, participants will be able to: Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches.
To realize reinforcement learning, deep learning and neural networks are used. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments.