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.


  • Time
    3 months

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

  • Classroom Opens
    30 April 2019

    Classroom opens 7 days after enrollment closes

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.

12 Month access*
30+ Nanodegree Programs
0% EMI
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
Anjishnu M.

I thoroughly enjoyed completing the exercises in parallel to the lecture videos, which is unique to the Udacity style of learning.

Carlos O.

One of the most incredible NDs ever! I've being learning more than a regular graduation. I am full of perspectives.

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.

Computer Vision

Introductory Price

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

Admissions Closes: 01 May, 2019

1000+ jobopportunities created
100+ Hiring partnersonboard
₹ 40 lac+ Highestannual CTC offered

Payment Options

We support multiple payment options for your convenience. Choose an option that suits you the most

Credit/Debit Card

Accepting payments through Credit/Debit cards from all major banks.

EMI on Credit Card

Split the payment of the course fee across 3 or more months. Option is available for all plans. Instalment information available on the payment page.

Internet Banking
Internet Banking

Seamless payment though Internet banking accepting payments from over 59 banks.


    Program Highlights
  • 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 kinds of topics will the program cover?
    This program covers a combination of classical and modern artificial intelligence techniques specific to computer vision. The program starts by exploring the fundamental math and programming concepts that drive pattern and object recognition tasks, such as image processing, image color and shape manipulation, feature detection, and convolutional neural network (CNN) architecture. Then, the program moves onto deep learning architectures that have led to state of the art advances in computer vision tasks, such as region-based CNN’s and recurrent neural networks for image captioning. Lastly, it covers object tracking and localization techniques that are necessary skills for those looking to get into the field of robotics and autonomous systems.
  • How are you developing the curriculum, and who are your partners?
    Udacity has developed the Computer Vision Nanodegree program in collaboration with NVIDIA, a cutting-edge deep learning and robotics company whose work relies on the computer vision techniques of scene understanding and robot localization. We have also collaborated with Affectiva, an emotion-recognition technology company that is contributing to the development of social robotics and emotionally intelligent systems.
  • 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.
  • 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.
  • I've 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.
  • Can I enroll in the program at any time?
    Yes! We admit students on a rolling basis, and you will automatically be added to the next available term once you’ve successfully enrolled. Depending on when you enroll, your term may start as late as four weeks after your enrollment date.
  • Can I enter the classroom prior to the start of my term?
    Yes, but you won't be able to access the content, as it stays locked until your term begins. In the classroom, you'll see a countdown to your term's start date.
  • Are deferments an option if I'm enrolled, but not ready to start yet?
    No, deferments are not an option. We ask that you please make sure to enroll for a term only if you are able to commit to the entire time frame.
  • 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?
  • Other Terms and Conditions
    This program is subject to special terms and conditions located on the legal hub. Please click on the “See “Special Terms” and select the terms and conditions related to this program.
    Program Structure
  • What happens if I don’t complete a project on time?
    It is strongly recommended that you complete each project on time to ensure you meet graduation requirements. To graduate, you must complete, submit, and meet expectations for all required projects by the final deadline . While there is no penalty for missing a project deadline, missing one puts you at risk to be removed from the program if you do not stay on track and complete all required projects before the term ends. Finally, by keeping pace with your fellow students, you'll gain much more value from forums and Slack channels!
  • What happens if I don't complete a term by the term deadline?
    You will receive a free four-week extension, which is automatically applied to your account if you do not complete the program within the term. If you do not complete the program within the extension, you will be removed from the program and will no longer be able to access course content. To resume access to the course, you would need to pay the term fee again. In such case, your progress will carry over, so you will be able to continue where you left off.
  • Will I have permanent access to the material even after the term ends?
    No. You will retain access to the program materials for a period of time after graduation and you may download certain materials for your own records if you wish. Please note however, that students who leave the program—or who are removed from the program for failure to meet the final deadlines—prior to successfully graduating, will cease to have access.
  • How many hours a week should I expect to spend on my coursework, in order to succeed in this program?
    Between instructional content, quizzes, projects, and other course-related activity, we estimate that investing 10 hours/week for 3 months will enable you to proceed through the program at a successful pace. Students with significant prior experience may spend less time, while students with very limited prior experience may require significantly more time.
    Career Services
  • Do I have access to Propel?
    Propel is the flagship Career Fair of Udacity in India. Only Advanced Job ready Nanodegree graduates have access to Propel. Through this initiative we connect our Nanodegree graduates to new-age technology companies and help them achieve their career goals.This is a foundation Nanodegree Program and the goal of the program is to build foundation skills in new-age technologies.
    Hence, Foundation Nanodegree Program Students do not have access to Propel.
  • How much does the Nanodegree program cost?
    This Nanodegree program consists of one three month term. The term costs INR 49900 paid at the beginning of the term.
  • Is payment due before the term begins?
    Yes. In this way, we know exactly how many student are in a term, and can optimize our instructional and support resources accordingly. Additionally, this approach ensures a consistent and stable student body throughout the program, which fosters a deeper sense of community, and enables richer collaborations as students work together as a group.
  • Is there an installment plan for tuition?
    No, the full tuition must be paid before the start of your term.
  • Is there a free trial period for this program?
    There is no free trial period for this program.
  • Are there any scholarships available for this program?
    All current scholarship opportunities are posted on our Scholarships page.
  • What is the refund policy?
    There is a 7-day refund policy. During this time, you can visit the Settings page of your Udacity classroom where you can unenroll and request a full refund. This 7-day window begins the day the classroom opens. After the first 7 days, course fees are non-refundable.
  • Will content from the program also be available for free outside of the Nanodegree program?
    While some of the video material is available outside of the program, most of the material will only be available to enrolled Nanodegree students. Access to project feedback, instructor support, and hiring partners are benefits exclusive to the Nanodegree programs.
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