New!
Time
1 Four-Month Term
Study 10-15 hrs/week and complete in 4 months.
Classroom Opens
April 23, 2019
Classroom opens 7 days after enrollment closes
In Collaboration with
Dream big. We’ll get you there!
Whatever your goals, Udacity is dedicated to helping you make them happen. Master the latest skills, build amazing projects, and advance your career. With our unrivaled support and personalized attention we’ll do everything we can to make sure you succeed. We’ve got the support you need to turn your dreams into reality.
Dedicated personal mentor
Overcome barriers to your learning with a knowledgeable mentor who can answer your questions and keep you focused on your goals.
Weekly live sessions
Get the close attention you need and interact with your classmates in regular live Q&A sessions and webinars.
Personalized learning plan
Accelerate your learning and beat your goals with a learning plan designed around your life.
Why Take This Nanodegree Program?
Deep reinforcement learning is one of AI’s hottest fields. Researchers, engineers, and investors are excited by its world-changing potential. In this advanced program, you’ll master techniques like Deep Q-Learning and Actor-Critic Methods, and connect with experts from NVIDIA and Unity as you build a portfolio of your own reinforcement learning projects.
Master the Most Cutting-Edge Techniques
Deep reinforcement learning is at the forefront of AI research. Many experts see it as a path to Artificial General Intelligence. In this advanced program, you’ll master the latest techniques: Deep Q-Learning, Actor-Critic Methods, and more.
Learn from the World’s Leading Experts
We collaborated with NVIDIA and Unity to build a world-class program that balances theory with practical application, and supports exploration of new approaches to compelling challenges in fields ranging from gaming to finance to robotics.
Design Your Own Algorithms
You’ll learn the theories behind the most recent advances in deep reinforcement learning, and then use that knowledge to train your own agents! You’ll complete three major projects, and build a strong portfolio in the process.
Get Personalized Project Reviews
Get personalized feedback on your projects from a team of AI experts. Then share your polished projects on GitHub, showcasing your mastery of this advanced field.
Learn with the best
Alexis Cook
Curriculum Lead
Alexis is an applied mathematician with a Masters in Computer Science from Brown University and a Masters in Applied Mathematics from the University of Michigan. She was formerly a National Science Foundation Graduate Research Fellow.
Arpan Chakraborty
Content Developer
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
Mat Leonard
Product Lead
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
Luis Serrano
Content Developer
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in Mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Cezanne Camacho
Content Developer
Cezanne is an expert in computer vision with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she’s applied computer vision and deep learning to medical diagnostic applications.
Dana Sheahen
Content Developer
Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.
Chhavi Yadav
Content Developer
Chhavi is a Computer Science graduate student at New York University, where she researches machine learning algorithms. She is also an electronics engineer and has worked on wireless systems.
Juan Delgado
Content Developer
Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.
Miguel Morales
Content Developer
Miguel is a software engineer at Lockheed Martin. He earned a Masters in Computer Science at Georgia Tech and is an Instructional Associate for the Reinforcement Learning and Decision Making course. He’s the author of Grokking Deep Reinforcement Learning.
What You Will Learn
Download SyllabusSyllabus
Deep Reinforcement Learning
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Prerequisite Knowledge
This program requires experience with Python, probability, machine learning, and deep learning.See detailed requirements.
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.
NavigationPolicy-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 ControlMulti-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
“Just as machines made human muscles a thousand times stronger, machines will make the human brain a thousand times more powerful.”— Sebastian Thrun
Student Reviews
Top Reviews
(27)
5 stars
74.1%
4 stars
14.8%
3 stars
7.4%
2 stars
3.7%
1 stars
0.0%
Markus B.
State-of-the-art program with extraordinary projects. Core of moder AI. Udacity opens new doors for people who wanr to change the world. Perfect
Junjie X.
还是可以学到很多干货的，但是要真的转行或者找工作，自己平时的努力和积累也是必不可少的
Farida H.
I loved how the research spirit was obvious in this nanodegree
Muh Alif A.
The materials are presented in a clear and elaborate way.
Robson M.
The program is very didactic, the lessons are detailed and I could learn very much with the projects. These are important adjectives because we are handling with a difficult subject.
Term 1
Deep Reinforcement Learning
$999 USD
total
Master cutting-edge deep reinforcement learning algorithms with hands-on coding exercises, and challenging, open-ended projects.
Success Stories from Our Students
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Deep Reinforcement Learning
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