Become a Computer Vision Expert

Nanodegree Program

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.

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Estimated time
3 Months
At 10-15 hrs/week
Enroll by
April 26, 2023
Get access to classroom immediately on enrollment
Skills acquired
SLAM, Object Tracking, Object Detection, Recurrent Neural Networks

In collaboration with

What you will learn

Foundations of Computer Vision
3 Months to complete
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.
Related Nanodegree programs
Prerequisite knowledge
This program requires experience with Python, statistics, machine learning, and deep learning.
1. 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.
2. 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.
3. 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.

All our programs include

Real-world projects from industry experts
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
Real-time support
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
Career services
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Flexible learning program
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program offerings

Student services
- Student community
- Real-time support
Career services
- Github review
- Linkedin profile optimization
Class Content
- Content co-created with Affectiva
- Real-world projects
- Project reviews
- Project feedback from experienced reviewers

Succeed with personalized services.

We provide services customized for your needs at every step of your learning journey to ensure your success.

Experienced Project Reviewers
Real-Time Support

Get timely feedback on your projects.

Personalized feedback
Unlimited submissions and feedback loops
Practical tips and industry best practices
Additional suggested resources to improve

1,400+
project reviewers
2.7M
projects reviewed
88/100
reviewer rating
1.1 hours
avg project review turnaround time

Learn with the best.

Sebastian Thrun
Instructor
As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.
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
Curriculum Lead
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
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
Instructor
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
Curriculum Lead
Ortal Arel has a PhD in Computer Engineering, and has been a professor and researcher in the field of applied cryptography. She has worked on design and analysis of intelligent algorithms for high-speed custom digital architectures.
Luis Serrano
Instructor
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.

Top student reviews

4.6

4.6 stars

(800)

Muhammad Sulaiman N.

5.0 stars

To be honest, at first I was extremely skeptical and thought that the Nanodegree might just be another knock off course like the ones on Udemy but I was surprised in a good way.

This degree encourages projects (and mini projects) in a more practical manner. Aside from the main projects, there are extra tasks in between to better my skills in this domain and its a welcoming thing.

I've gained more insights than I could ever before with simple and short explanations followed by coding notebooks. This has allowed me to bridge the gap between theory and practice.

Overall, the program feels fulfilling and satisfactory. Would definitely recommend this to a friend!

Carlos M.

5.0 stars

I feel kind of frustrated with the low pace I am taking this course. I come from NDs where the learning curve you take is paired with the lessons. When I find these lessons there is a lot of knowledge in there. I work hard and memorize parts of them in order to learn from them. But I feel there's hard work behind the scenes with it. And personally I find myself tired of this work. You're presented with a lot of knowledge impossible to grasp; print all the work; prove to apply it myself; etc. It is tiresome... I hope to do it well in the future but I have spent many months this way and feel like to expedite this pace... Thanks!

Jose A.

5.0 stars

It is difficult to follow the pace to achieve the program in three months, due to the current COVID circumstances: work, parenting a 1 year old kid and following the lessons/projects is very challenging. I wish I had more time to dedicate to the projects and courses, like the optional topics and tasks, but sadly it is not the case.

Other than that, I find it very interesting, the material is very useful, specially that optional task of creating your own deep-nn, and the existence of the knowledge database is also great to find my concerns shared by many other people.

Kudos for your great work putting all this together!

Amit S.

5.0 stars

Pretty much all that I needed and even more. The course is very well structured and there almost no cons for the same. But the subscription cost is too damn high. Students in developing countries like India can't afford this much. The amount you charge for a month is equivalent to an Indian fresher's one month salary. So, even if a fresher wants to skill up using your platform, they would probably pass. It's like this platform is just for the privileged, for those who have the pockets to afford such an amount. Even a 50% discount doesn't seem generous enough to make the course look affordable.

Taesoo C.

5.0 stars

Everything was the first. I was first exposed to Jupyter, Pytorch, OpenCV, all the image processing theories, Deep Learning and CNN. The learning curve was very steep and I am still trying to understand them and connect the dots among them. Image processing is the essential part of our daily lives and it will be ever more important in the days coming. My curiosity on computer vision is being sated by this course and I hope I can help some animal protection NGOs with the knowledge I have learned. I am really appreciate your efforts to fit everything together to learn the computer vision.

Pranjal C.

5.0 stars

Exceptionally well rounded and wholesome introduction to Computer Vision methods going from the very basic 'classical' OpenCV based techniques to all the way to sophisticated Deep Learning based applications. However, I do wish that Udacity 'updates' this course soon as the state of the art techniques discussed have changed a lot since 2017-18. After the completion of this ND, you'd be deft with state of the art advances in Computer Vision that have happened around till late 2017/early 2018. I would still give this ND a 5-star rating because it is so well made!

Computer Vision

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Monthly access
Pay as you go

¥ 42679
per month

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- Maximum flexibility to learn at your own pace.
- Cancel anytime.
3-Month access
Pay upfront and save an extra 14%

¥ 108837 ~~¥ 128037~~
for 3-Month access

Enroll now
- Save an extra 14% vs. pay as you go.
- 3 months is the average time to complete this course.
- Switch to monthly price after if more time is needed.
- Cancel anytime.
Best Value

Learn
Learn the essentials of computer vision, including image transformation, neural network architectures, and object recognition
Average Time
On average, successful students take 3 months to complete this program.
Benefits include
- Real-world projects from industry experts
- Real-time classroom support
- Career services

Program Details

Program overview: Why should I take this program?

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.

Enrollment and admission

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?

Tuition and term of program

How is this Nanodegree program structured?
The Computer Vision Nanodegree program is comprised of content and curriculum to support three (3) projects. We estimate that students can complete the program in three (3) months working 10 hours per week.

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 length of time specified above. If you do not graduate within that time period, you will continue learning with month-to-month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.
Can I switch my start date? Can I get a refund?
Please see the Udacity Program FAQs 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.

Software and hardware: What do I need for this program?

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.