Study 10-15 hrs/week and complete in 3 months.
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!
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!
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.
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.
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!
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This program requires experience with Python, statistics, machine learning, and deep learning.See detailed requirements.
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
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
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
Sebastian Thrun is a scientist, educator, inventor, and entrepreneur. Prior to founding Udacity, he launched Google’s self-driving car project.
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 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 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 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 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 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.
Very practical, I learnt a lot from this experience.
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.
Great program, can recommend this to everyone.
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.
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 !!
Learn the essentials of computer vision, including image transformation, neural network architectures, and object recognition
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.
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.
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.
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
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:
Basic shell scripting:
Basic statistical knowledge, including:
Intermediate differential calculus and linear algebra, including:
We have a number of courses and programs we can recommend that will help prepare you for the program, depending on the areas you need to address. For example:
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.
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
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.
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.