[Udacity] Computer Vision Nanodegree v1.0.0

NANODEGREE PROGRAM–nd891

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.

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

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.

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

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.

Size: 2.65G

 

 

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