Deep Reinforcement Learning Nanodegree Program

Intermediate to advanced Python experience

You are familiar with object-oriented programming

You can write nested for loops and can read and understand code written by others

Apply deep learning architectures to reinforcement learning tasks

Design your own algorithm to train a simulated robotic arm to reach target locations

Learn how to apply reinforcement learning methods to applications that involve multiple, interacting agents

Learn the theory behind evolutionary algorithms and policy-gradient methods

Master the fundamentals of reinforcement learning by writing your own implementations of many classical solution methods

These techniques are used in a variety of applications, such as the coordination of autonomous vehicles

Train your own agent that navigates a virtual world from sensory data

This Nanodegree program accepts all applicants regardless of experience and specific background