Enroll by August 14!
Study 12 hrs/week and complete in 4 mo.
Learning material and communication in English
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.
Learn practical skills taught by deep learning experts including Sebastian Thrun, Ian Goodfellow, Andrew Trask, and the Udacity Deep Learning Team.
Work on five specially-designed deep learning projects, and receive detailed feedback on each from our expert reviewers.
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.
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This program has been created specifically for students who are interested in machine learning, AI, and/or deep learning, and who have a working knowledge of Python programming, including numpy and pandas. Outside of that Python expectation and some familiarity with calculus and linear algebra, it's a very beginner-friendly program.See detailed requirements.
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 modern deep learning frameworks (Keras, TensorFlow) to build multi-layer neural networks, and analyze real data.Your First Neural Network
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.Dog-Breed Classifier
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.Generate TV scripts
Learn to understand and implement the DCGAN model to simulate realistic images, with Ian Goodfellow, the inventor of GANS (generative adversarial networks).Generate Faces
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.Teach a Quadcopter How to Fly
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.
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.
To make it even easier to learn, you can finance your Nanodegree through Affirm.
As low as US$84 per month at 0% APR.
Pay your monthly bill using a bank transfer, check, or debit card.
Learn to build the deep learning models that are revolutionizing artificial intelligence.
In this program, you’ll master deep learning fundamentals that will prepare you to launch or advance a career, and additionally pursue further advanced studies in the field of artificial intelligence. You will study cutting-edge topics such as neural, convolutional, recurrent neural, and generative adversarial networks, as well as sentiment analysis model deployment. You will build projects in Keras and NumPy, in addition to TensorFlow PyTorch. You will learn from experts in the field, and gain exclusive insights from working professionals. For anyone interested in building expertise with this transformational technology, this Nanodegree program is an ideal point-of-entry.
This program is designed to build on your skills in deep learning. As such, it doesn't prepare you for a specific job, but expands your skills in the deep learning domain. These skills can be applied to various applications and also qualify you to pursue further studies in the field.
If you are interested in the fields of artificial intelligence and machine learning, this Nanodegree program is the perfect way to get started!
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
Students who are interested in enrolling must have intermediate-level Python programming knowledge, and experience with NumPy and pandas. You will need to be able to communicate fluently and professionally in written and spoken English. Additionally, students must have the necessary math knowledge, including: algebra and some calculus—specifically partial derivatives, and matrix multiplication (linear algebra).
We have a number of Nanodegree programs and free courses that can help you prepare, including:
The Deep Learning Nanodegree program is comprised of one (1) Term of four (4) months. A Term has fixed start and end dates.
To graduate, students must successfully complete five (5) projects, each of which affords you the opportunity to apply and demonstrate new skills that you learn in the lessons. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
Graduates from this Nanodegree program earn guaranteed admitted status into our more advanced Self-Driving Car Engineer or Flying Car Nanodegree programs, subject to payment by student for the cost of enrollment for those Nanodegree programs.
Some Nanodegree programs, due to the complexity of the material, require prerequisites and/or an application process to ensure that students who enroll are qualified to meet the demands of the course. However, in those instances where students have graduated from other Udacity courses that we feel adequately prepare them for our more advanced courses, we will guarantee that they will be allowed to enroll subject to paying the Nanodegree program fees.
Virtually any 64-bit operating with at least 8GB of RAM will be suitable. Students should also have Python 3 and Jupyter Notebooks installed. For the more intensive portions of the program that come later, we will be providing students with AWS instances where geographically possible.