Deep learning is driving advances in artificial intelligence that are changing our world. Enroll now to build and apply your own deep neural networks to produce amazing solutions to important challenges.
Study 12 hrs / week
Become career-ready faster
INDUSTRY SIZE & DEMAND
Deep Learning Market is expected to grow at the CAGR of 52.1% till 2025
Demand for AI, DL and ML specialists in the country are expected to see a 60% rise by 2018 due to increasing adoption of automation
RANKED #08 CNBC
Udacity ranked as the most disruptive learning company in the world for 2 years in a row by CNBC
Join a global community of over 50,000 Deep Learning Engineers who have learned with Udacity
Our Hiring Partners in Deep Learning
Prerequisites and Requirements
You’ll need intermediate experience with Python to start this program. Some basic knowledge of machine learning is beneficial, although not required, to start this program.
Prepare now with AI Programming with Python.
WHAT YOU LEARN
Study cutting edge Content
Deep Learning Nanodegree
In this term, you’ll build and apply your own deep neural networks to produce amazing solutions to important challenges.
Best in-class content by industry leaders in the form of bite-size videos and quizzes.
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.
Learn neural networks basics, and build your first network with Python and NumPy. Use the modern deep learning framework PyTorch to build multi-layer neural networks, and analyze real data.
Convolutional Neural Networks
Learn how to build convolutional networks and use them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in them. Use these networks to learn data compression and image denoising.
Recurrent Neural Networks
Build your own recurrent networks and long short-term memory networks with PyTorch; perform sentiment analysis and use recurrent networks to generate new text from TV scripts.
Generative Adversarial Networks
Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs.
Deploying a Sentiment Analysis Model
Train and deploy your own PyTorch sentiment analysis model. Deployment gives you the ability to use a trained model to analyze new, user input. Build a model, deploy it, and create a gateway for accessing it from a website.
Industry relevant projects + unlimited project reviews by our global reviewers
Predicting Bike-Sharing Patterns
Generate TV scripts
Deploying a Sentiment Analysis Model
We guide and support you throughout your learning journey through these services.
Search-based Q&A forum
Collaborate with Fellow Students
Project reviews & feedback
Receive actionable feedback from expert project reviewers until you get your code right!
Your Nanodegree journey
ENROLL IN NANODEGREE PROGRAM
enroll by 13 Feb 2019
BRUSH UP ON PRE-REQUISITES
while you wait for classroom to open, brush up on pre-requisites
classroom will open on 13 Feb 2019In case you feel unsure about the program, we offer a full refund on cancelling within 7 days of classroom opening.
submit all projects within 4 months
COMPLETE NANODEGREE PROGRAM
finish requirements for graduation
You are eligible to take part in our career fest Propel.
Learn from top Industry Experts
Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
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 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 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 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.
Land your dream Deep Learning career
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