Nanodegree Program
Become a Deep Reinforcement Learning Expert
In Collaboration with
Program Details
Time
1 Term4 monthsSuggested study
10-15 hrs/week to complete in 4 mo.Skills learned
Deep Reinforcement LearningDeep Neural NetworksConvolutional Neural NetworksPyTorchQ-Learning
About the 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.
Apple, Facebook, and Google are investing in deep reinforcement learning.What You Get with a Nanodegree Program
Industry Experts
Hands-on learning of the most important job skills taught by industry experts
Real World Projects
Industry-designed projects that help you build your portfolio
Community Mentoring
Global mentors evaluate projects and provide support throughout the program
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'll Learn with this Nanodegree Program
Term 1
Deep Reinforcement Learning
More details
Prerequisite Knowledge
This program requires experience with Python, probability, machine learning, and deep learning.
Concepts You'll Learn
Foundations of Reinforcement Learning
Value-Based Methods
Policy-Based Methods
Multi-Agent Reinforcement Learning
Learn Now, Pay Later with Affirm
To make it even easier to learn, you can finance your Nanodegree Program through Affirm.
Easy monthly payments
As low as $84 per month at 0% APR.
Flexible Payments
Pay your monthly bill using a bank transfer, check, or debit card.
Enroll Today and Start Class on September 26
Frequently Asked Questions
FAQ
Why should I enroll?
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.What jobs will this program prepare me for?
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.How do I know if this program is right for me?
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.
Program Overview - Why Should I Take this Program?
Do I need to apply? What are the admission criteria?
No. This Nanodegree program accepts all applicants regardless of experience and specific background.What are the prerequisites for enrollment?
We recommend that you complete a course in Deep Learning equivalent to the Deep Learning Nanodegree program prior to entering the program. You will need to be able to communicate fluently and professionally in written and spoken English.
Additionally, you should have the following knowledge:
- Intermediate Python programming knowledge, including:
- Strings, numbers, and variables
- Statements, operators, and expressions
- Lists, tuples, and dictionaries
- Conditions, loops
- Generators & comprehensions
- Procedures, objects, modules, and libraries
- Troubleshooting and debugging
- Research & documentation
- Problem solving
- Algorithms and data structures
Basic shell scripting:
- Run programs from a command line
- Debug error messages and feedback
- Set environment variables
- Establish remote connections
Basic statistical knowledge, including:
- Populations, samples
- Mean, median, mode
- Standard error
- Variation, standard deviations
- Normal distribution
Intermediate differential calculus and linear algebra, including:
- Derivatives & Integrals
- Series expansions
- Matrix operations through eigenvectors and eigenvalues
If I do not meet the requirements to enroll, what should I do?
We have a number of Nanodegree programs and free courses that can help you prepare, including:
Enrollment and Admission
How is this Nanodegree program structured?
The Deep Reinforcement Learning Nanodegree program consists of one four-month long term. All students must successfully complete three projects in order to graduate. Each project will be reviewed by one of the project reviewers in the Udacity reviewer network. Your reviewer will give you detailed feedback on your work and let you know where your project needs improvement, if necessary. If you do not pass the project, you will be asked to submit again until you pass in order to successfully complete the term.How long is this Nanodegree program?
Access to this Nanodegree program runs for the period noted in the Term length section above.
See the Terms of Use and FAQs for other policies around the terms of access to our Nanodegree programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
Tuition and Term of Program
What software and versions will I need in this program?
You will need a computer running a 64-bit operating system (most modern Windows, OS X, and Linux versions will work) with at least 8GB of RAM, along with administrator account permissions sufficient to install programs including Anaconda with Python 3.6 and supporting packages. Your network should allow secure connections to remote hosts (like SSH). We will provide you with instructions to install the required software packages.
Software and Hardware - What Do I Need for This Program?
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