// 4 courses indexed
The course directory
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Deep Reinforcement Learning: From Theory to Practice
How can reinforcement learning scale beyond small tabular problems to high-dimensional environments such as games, robotics, and autonomous decision-making? This course introduces deep reinforcement learning, where reinforcement-learning algorithms are combined with neural-network-based function approximation. Learners begin by studying why tabular methods break down in large or continuous state spaces and how value functions, action-value functions, and policies can be represented by parameterized models. The course then develops value-based deep reinforcement learning methods, including fit
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Adding Electronics to Rapid Prototypes
Hello, everyone! Welcome to this course on Adding Electronics to Rapid Prototypes. This is part of the Rapid Prototyping and Tooling specialization. In this course, I’ll cover the basics of electric circuits, breadboards, and multimeters. I’ll then discuss different options for connecting electrical components as well as discuss different types of motors and actuators. Finally, I’ll end this course by discussing microcontrollers and how to use them to make even more sophisticated prototypes. By exploring both electrical simulations and many examples from different robotics projects I’ve had t
All levels