• Time
    1 Four-Month Term

    Study 12 hrs/week and complete in 4 mo.

  • Classroom Opens
    January 09, 2018

    Classroom opens in 27 days.

  • Student Rating

    View all reviews ()

Why Take This Nanodegree Program?

In this program, you’ll cover topics like Keras and TensorFlow, convolutional and recurrent networks, deep reinforcement learning, and GANs. You'll learn from authorities such as Sebastian Thrun, Ian Goodfellow, and Andrew Trask, and enjoy access to Experts-in-Residence from OpenAI, Google Brain, DeepMind, Bengio Lab and more. This is the ideal point-of-entry into the field of AI.

Icon arrow stat

AI-driven global software revenue will top
$30B
in 2020

Features 1
Amazing content & live sessions

Expert Instructors

Learn practical skills taught by deep learning experts including Sebastian Thrun, Ian Goodfellow, Andrew Trask, and the Udacity Deep Learning Team.

Projects with expert feedback

Unique Projects, Personalized Feedback

Work on five specially-designed deep learning projects, and receive detailed feedback on each from our expert reviewers.

Features 2
Guaranteed Admission

Guaranteed Admission

Successfully complete the program, and receive guaranteed admission to our Self-Driving Car Engineer, Artificial Intelligence, or Robotics Nanodegree programs!

Practical Career Support

Office Hours with Udacity Experts-in-Residence

Enjoy direct access to world-class deep learning practitioners from some of the most innovative organizations in the world. Moderated office hour sessions offer practical, actionable, and insightful guidance and support.

Guaranteed Admission

As a graduate, you earn guaranteed admission into one of three advanced Nanodegree programs. You’ll continue to explore even more deep learning projects alongside groundbreaking new curriculum built with our pioneering industry collaborators. This is how you transform into a job-ready specialist!

Step 1

Enroll in the Deep Learning Nanodegree Foundation program

Step 2

Graduate within 4 months

Step 3

Enroll in one of three advanced Nanodegree programs with guaranteed admission

Office Hours with our Experts-in-Residence

Benefit from the opportunity to connect directly with our Udacity Experts-in-Residence, an elite group of deep learning practitioners working at some of the most innovative organizations in the world, including OpenAI, GoogleBrain, DeepMind, Bengio Lab and more. In moderated office hour sessions, you’ll get actionable insights and guidance that will power your progress through the program, and help prepare you for the next steps in your deep learning future.

Our Udacity Experts-in-Residence

Tom Brown

Google Brain

Anirudh Goyal

Bengio Lab

Adhiguna Kuncoro

DeepMind/Oxford

Jules Pondard

Bengio Lab

Sandeep Subramanian

Bengio Lab

Our world-class Udacity faculty

expert[:name]
Sebastian Thrun
Founder, Google X, Self-Driving Car pioneer
expert[:name]
Ian Goodfellow
Inventor of GANs, author of Deep Learning (MIT Press)
expert[:name]
Andrew Trask
Author of Grokking Deep Learning, Oxford Scholar
expert[:name]
Siraj Raval
AI Evangelist, Author, Entrepreneur, and Educator

Learn with the Best

Mat Leonard
Mat Leonard

Program 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
Luis Serrano

Curriculum Lead

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.

Alexis Cook
Alexis Cook

Instructor

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.

Ortal Arel
Ortal Arel

Instructor

Ortal Arel is a former computer engineering professor. She holds a Ph.D. in Computer Engineering from the University of Tennessee. Her doctoral research work was in the area of applied cryptography.

Arpan Chakraborty
Arpan Chakraborty

Instructor

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.

Jay Alammar
Jay Alammar

Instructor

Jay is a software engineer, the founder of Qaym (an Arabic-language review site), and the Investment Principal at the Riyad Taqnia Fund, a $120 million venture capital fund focused on high-technology startups.

What You Will Learn

Syllabus

Deep Learning

Become an expert in neural networks, and learn to implement them in Keras and TensorFlow. Build convolutional networks for image recognition, recurrent networks for sequence generation, generative adversarial networks for image generation, and more.

Master building and implementing neural networks for image recognition, sequence generation, image generation, and more.

See Details

4 months to complete

Prerequisite Knowledge

This program requires experience with Python and packages such as Numpy and Pandas. You’ll also need to be familiar with algebra, calculus (multivariable derivatives) and linear algebra (matrix multiplication). See detailed requirements.

  • Introduction

    Get your first taste of deep learning by applying style transfer to your own images, and gain experience using development tools such as Anaconda and Jupyter notebooks.

  • Neural Networks

    Learn neural networks basics, and build your first network with Python and Numpy. Use modern deep learning frameworks (Keras, TensorFlow) to build multi-layer neural networks, and analyze real data.

    Icon project Your first neural network
  • Convolutional Neural Networks

    Learn how to build convolutional networks and use them to classify images (faces, melanomas, etc.) based on objects that appear in them. Use these networks to learn data compression and image denoising.

    Icon project Dog-Breed Classifier
  • Recurrent Neural Networks

    Build your own recurrent networks and long short-term memory networks with Keras and TensorFlow; perform sentiment analysis and generate new text. Use recurrent networks to generate new text from TV scripts.

    Icon project Generate TV scripts
  • Generative Adversarial Networks

    Learn to understand and implement the DCGAN model to simulate realistic images, with Ian Goodfellow, the inventor of GANS (generative adversarial networks).

    Icon project Generate Faces
  • Deep Reinforcement Learning

    Use deep neural networks to design agents that can learn to take actions in a simulated environment. Apply reinforcement learning to complex control tasks like video games and robotics.

    Icon project Teach a Quadcopter How to Fly

Start Learning Now

Deep Learning

total

Learn to build the deep learning models that are revolutionizing artificial intelligence.

Start Learning Now

“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

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FAQ

  • What is a "Nanodegree Foundation program", and how does it differ from your existing Nanodegree programs?

    A Nanodegree Foundation program is designed to power your entry into a particular arena of study, with the goal of ensuring that you establish a solid "foundation" in the field. Depending on your longer-term goals, a Nanodegree Foundation program can enhance your existing skillset, help move you forward into advanced studies, or advance your career.

See More Questions

Start Building Your Deep Learning Foundations Today

Enroll today, and start putting your skills to work!

Start Learning Now
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