Nanodegree Program

Become a Computer Vision Expert

Master the computer vision skills behind advances in robotics and automation. Write programs to analyze images, implement feature extraction, and recognize objects using deep learning models.

Enrollment Closing In

  • Time
    1 Three-Month Term

    Study 10-15 hrs/week and complete in 3 months.

  • Classroom Opens
    January 29, 2019
In Collaboration with
  • Affectiva
  • Nvidia DLI

Why Take This Nanodegree Program?

From computer graphics to social robotics to autonomous vehicles, computer vision is powering world-changing new technologies. In this program, you’ll write code to perform everything from facial recognition to scene-understanding to object tracking; by the end of this program, you’ll have a broad portfolio of applications that you’ve built!

Why Take This Nanodegree Program?

Employer demand for AI-related roles has more than doubled over the past three years.

Learn the Most Cutting-Edge Techniques
Learn the Most Cutting-Edge Techniques

Learn the Most Cutting-Edge Techniques

Computer vision is a rapidly growing field that powers a variety of emerging technologies—from facial recognition to augmented reality to self-driving cars. Learn the latest deep learning architectures and image processing techniques today!

Built in Collaboration with Industry

Built in Collaboration with Industry

We collaborated with industry leaders from NVIDIA to Affectiva to build a program that showcases how computer vision is being applied on the front-lines of technology today.

Code Your Own Computer Vision Apps
Code Your Own Computer Vision Apps

Code Your Own Computer Vision Apps

You’ll learn how to program computer vision techniques in Python, and then use that knowledge to create your own applications! You’ll complete three major computer vision projects, and build a strong portfolio in the process.

Personalized Project Reviews

Personalized Project Reviews

Get personalized feedback on your computer vision projects from a team of technical reviewers. The invaluable reviews you receive mirror the experience of working on a team of engineers and mentors, and this feedback offers you unique and actionable insights as to how you should develop code!

What You Will Learn

Download Syllabus

Foundations of Computer Vision

Learn cutting-edge computer vision and deep learning techniques—from basic image processing, to building and customizing convolutional neural networks. Apply these concepts to vision tasks such as automatic image captioning and object tracking, and build a robust portfolio of computer vision projects.

Work on a variety of computer vision and deep learning applications from basic image processing to automatic image captioning.

See fewer details

3 Months to complete

Prerequisite Knowledge

This program requires experience with Python, statistics, machine learning, and deep learning.See detailed requirements.

  • Introduction to Computer Vision

    Master computer vision and image processing essentials. Learn to extract important features from image data, and apply deep learning techniques to classification tasks.

    Facial Keypoint Detection
  • Advanced Computer Vision and Deep Learning

    Learn to apply deep learning architectures to computer vision tasks. Discover how to combine CNN and RNN networks to build an automatic image captioning application.

    Automatic Image Captioning
  • Object Tracking and Localization

    Learn how to locate an object and track it over time. These techniques are used in a variety of moving systems, such as self-driving car navigation and drone flight.

    Landmark Detection & Tracking
A lot of the future of search is going to be about pictures instead of keywords. Computer vision technology is going to be a big deal.
— Ben Silbermann, CEO, Pinterest

Learn with the best

Sebastian Thrun
Sebastian Thrun

Udacity President

Sebastian Thrun is a scientist, educator, inventor, and entrepreneur. Prior to founding Udacity, he launched Google’s self-driving car project.

Cezanne Camacho
Cezanne Camacho

Curriculum Lead

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.

Alexis Cook
Alexis Cook

Content Developer

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.

Juan Delgado
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.

Jay Alammar
Jay Alammar

Content Developer

Jay has a degree in computer science, loves visualizing machine learning concepts, and is the Investment Principal at STV, a $500 million venture capital fund focused on high-technology startups.

Ortal Arel
Ortal Arel

Content Developer

Ortal Arel has a PhD in Computer Engineering, and has been professor and researcher in the field of applied cryptography and embedded platforms. She has worked on design and analysis of intelligent algorithms for high-speed custom digital architectures.

Luis Serrano
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.

Student Reviews



5 stars
4 stars
3 stars
2 stars
1 stars
Ho Yiu C.

Very practical, I learnt a lot from this experience.

Akira K.

It was very good that I could get familiarized with OpenCV library, and deep learning (CNN/RNN) with PyTorch. It was also very good that this program covers the latest topics, such as YOLO and SLAM. Lesson explanations are very carefully made and I could learn difficult concepts step by step.

Christian O.

Great program, can recommend this to everyone.

Ramy Raafat Mohamed Fawzy Ahmed W.

The program exceeded my expectation to be honest, I learned a lot and it was lots of fun. What was really good as well was the extra feedback on how your models can be improved. I appreciated the course a lot and thanks to everyone who participated in the program on the teaching/logistics side, it was a great experience.

Yohanssen P.

This program help me to improve my knowledge in computer vision. The video is easy to understand but also give a foundation to work on some challenging projects. Great program overall !!

Computer Vision
$999 USD


Learn the essentials of computer vision, including image transformation, neural network architectures, and object recognition

Program Details

  • Why should I enroll in this program?

    The demand for engineers with computer vision and deep learning skills far exceeds the current supply. This program offers a unique opportunity to develop these in-demand skills and is for anyone seeking to launch or advance their skills in modern computer vision techniques. You’ll complete several computer vision applications using a combination of Python, computer vision, and deep learning libraries that will serve as portfolio pieces that demonstrate the skills you’ve acquired.

  • What jobs will this program prepare me for?

    This program is designed to build on your skills in machine learning and deep learning. As such, it doesn't prepare you for a specific job, but expands your skills in the computer vision domain. These skills can be applied to various applications such as image and video processing, automated vehicles, smartphone apps, and more.

  • How do I know if this program is right for me?

    If you’re new to Computer Vision, and eager to explore applications like facial recognition and object tracking, the Computer Vision Nanodegree program is an ideal choice. The curriculum introduces you to image analysis with Python and OpenCV, then goes on to cover deep learning techniques that can be applied to a variety of image classification and regression tasks. Over the course of the program, you’ll leverage your Python coding experience to build a broad portfolio of applications that showcase your newly-acquired Computer Vision skills.

  • 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?

    You must have completed a course in Deep Learning equivalent to the Deep Learning Nanodegree program prior to entering the program. 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 don’t meet the requirements to enroll, what should I do?
  • How is this Nanodegree program structured?

    The Computer Vision Nanodegree program is composed of one (1) Term of three (3) months. A Term has fixed start and end dates.

    To graduate, students must successfully complete all projects as set forth in the syllabus, 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.

  • 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 Services 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.

  • I have graduated from the Computer Vision Nanodegree program but I want to keep learning. Where should I go from here?

    Many of our graduates continue on to our Artificial Intelligence Nanodegree program, Natural Language Processing Nanodegree Program, Robotics Engineer Nanodegree program, and our Self-Driving Car Engineer Nanodegree programs. Feel free to explore other Nanodegree program options as well.

  • 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 3.5 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. Udacity does not provide any hardware.