Deep Reinforcement Learning

Online Course

Udacity
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Deep Reinforcement Learning
  1. What is the course about?
  2. Prerequisites & Facts
  3. Cost, Certificate & Degree
  4. Reviews & Experiences

What is the course about?

Deep Reinforcement Learning
The course Deep Reinforcement Learning is an online class provided by Udacity. It may be possible to receive a verified certification or use the course to prepare for a degree.

Learn the deep reinforcement learning skills that are powering amazing advances in AI. Then start applying these to applications like video games and robotics.

Course description
  • Deep Reinforcement Learning
  • 4 Months (10-15 hrs/week)
  • Learn cutting-edge deep reinforcement learning algorithms—from Deep Q-Networks (DQN) to Deep Deterministic Policy Gradients (DDPG). Apply these concepts to train agents to walk, drive, or perform other complex tasks, and build a robust portfolio of deep reinforcement learning projects.
  • Write your own implementations of many cutting-edge algorithms, including DQN, DDPG, and evolutionary methods.
  • This program requires experience with Python, probability, machine learning, and deep learning.See detailed requirements.
  • Master the fundamentals of reinforcement learning by writing your own implementations of many classical solution methods.
  • Apply deep learning architectures to reinforcement learning tasks. Train your own agent that navigates a virtual world from sensory data.
  • Learn the theory behind evolutionary algorithms and policy-gradient methods. 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. These techniques are used in a variety of applications, such as the coordination of autonomous vehicles.
  • We recommend our Deep Learning Nanodegree program.
  • We recommend our Deep Learning Nanodegree program.
  • Foundations of Reinforcement Learning
  • Master the fundamentals of reinforcement learning by writing your own implementations of many classical solution methods.
  • Value-Based Methods
  • Apply deep learning architectures to reinforcement learning tasks. Train your own agent that navigates a virtual world from sensory data.
  • Navigation
  • Policy-Based Methods
  • Learn the theory behind evolutionary algorithms and policy-gradient methods. Design your own algorithm to train a simulated robotic arm to reach target locations.
  • Continuous Control
  • Multi-Agent Reinforcement Learning
  • Learn how to apply reinforcement learning methods to applications that involve multiple, interacting agents. These techniques are used in a variety of applications, such as the coordination of autonomous vehicles.
  • Collaboration and Competition
  • This program requires experience with Python, probability, machine learning, and deep learning.
  • The demand for engineers with reinforcement learning and deep learning skills far exceeds the number of engineers with these skills. This program offers a unique opportunity for you to develop these in-demand skills. You’ll implement several deep reinforcement learning algorithms using a combination of Python and deep learning libraries that will serve as portfolio pieces to demonstrate the skills you’ve acquired. As interest and investment in this space continues to increase, you’ll be ideally positioned to emerge as a leader in this groundbreaking field.
  • This program is designed to build on your existing skills in machine learning and deep learning. As such, it doesn’t prepare you for a specific job, but instead expands your skills in the deep reinforcement learning domain. These skills can be applied to various applications such as gaming, robotics, recommendation systems, autonomous vehicles, financial trading, and more.
  • This program offers an ideal path into the world of deep reinforcement learning—a transformational technology that is reshaping our future, and driving amazing new innovations in Artificial Intelligence. If you’re interested in applying AI to fields such as gaming, robotics, autonomous systems, and financial trading, this is the perfect way to get started.
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Prerequisites & Facts

Deep Reinforcement Learning

Course Topic

Fitness, Health & Fitness

University, College, Institution

Udacity

Course Skill Level

see course summary

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

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Degree & Cost

Deep Reinforcement Learning

To obtain a verified certificate from Udacity you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate (399 USD) or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
Udacity
Deep Reinforcement Learning
provided by Udacity
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School: Udacity
Topic: Computer Science, Deep Learning

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