Deep Reinforcement Learning

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

  • 1 Term

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  • 4 Months

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  • Study 10-15 hrs / week

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Admission closes on

Co - Created With

  • Unity
  • NVIDIA Deep Learning Institute

Why Enroll

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What You Learn

Study cutting edge Content

Pre-requisites : In order to succeed in this Nanodegree program, we strongly recommend that you have following prerequisites.
  • Intermediate to advanced Python experience. You are familiar with object-oriented programming. You can read and understand code written by others.
  • Intermediate statistics background. You are familiar with probability.
  • Intermediate knowledge of machine learning techniques. You can describe backpropagation, and have seen multiple
  • examples of neural network architectures (like a CNN for image classification).
  • You have seen or worked with a deep learning framework like TensorFlow, Keras, or PyTorch.
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In case you feel unsure about the program, we offer a full refund on cancelling within 7 days of classroom opening.
  • Term 1

    Term 1 : Deep Reinforcement Learning

    Master cutting-edge deep reinforcement learning algorithms with hands-on coding exercises, and challenging, open-ended projects.

    • Duration

      4 Months

    • Classroom Opens

      -

    • Term Fee

      ₹ 49900

Deep Reinforcement Learning

Term fee includes

Course content

Best in-class content by industry leaders in the form of bite-size videos and quizzes.

Course Syllabus
  • 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.

  • 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.

  • 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.

projects

Industry relevant projects + unlimited project reviews by our global reviewers

  • Navigation
  • Continuous Control
  • Collaboration and Competition

services

We guide and support you throughout your learning journey through these services.

Knowledge
  • Search-based Q&A forum
Study Groups
  • Collaborate with Fellow Students
Project reviews & feedback
  • Receive actionable feedback from expert project reviewers until you get your code right!

Instructors

Learn from top Industry Experts

Graduation Benefits

Graduate to unlock Benefits

After you successfully complete all terms

  • Industry recognized Nanodegree Certification

    Nanodegree certification recognized and valued by top companies in India

  • Career fair & career services

    Access to a hiring partner network of over 100 companies & Udacity Propel - our flagship career fair

    Learn more
  • Rs. 5,000 Udacity credits to continue learning

    A small incentive for you to come back and continue your learning with another Nanodegree program

CAREER PROSPECTS

Amazing Job Prospects

Deep Learning has 1000+ jobs posted on Naukri.com in a month

Turbocharge your salary

Deep Learning Engineers earns an average salary in the range of INR 6-20 Lakhs In India

Top-rated jobs

Deep Learning engineers empower technologies like Self Driving Car, Computer Vision and many others

FREQUENTLY ASKED QUESTIONS

Get Answers

FAQ

    Program Overview - Why Should I Take this Program?
  • 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.
    Enrollment and Admission
  • 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?
    Tuition and Term of Program
  • 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.
    Software and Hardware - What Do I Need for This 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.
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