Computer Vision

Master the core computer vision skills advancing robotics and automation

It's not too late to join 100,000+ students from 160+ countries who have already taken our programs.

Enrollment Deadline:

Program Starts:
September 15, 2022

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Course Dates

STARTS ON

September 15, 2022

Course Duration

DURATION

10 weeks, online
5-10 hours per week

Course Fee

PROGRAM FEE

US$2,500 US$2,300 or get US$250 off with a referral

Course Information Flexible payment available
program fee

US$2,500 US$2,300

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Dive Into the World of Computer Vision

With advances in machine learning (ML), the field of computer vision and its applications are growing by leaps and bounds, triggering transformations across industries and in daily life. Computer Vision is an online program offered by the Executive Education division of Carnegie Mellon University’s School of Computer Science. It enables software developers, ML engineers, and technology professionals to expand their knowledge with computer vision and image processing skills to become truly future-ready.

#1 in Artificial Intelligence Specialty and Graduate Programs for Computer Science.

Source: U.S. News & World Report

Key Takeaways

This is a 10-week online program designed to provide software developers, technology professionals, data scientists, data analysts, and ML professionals with an understanding of computer vision concepts, tools, and techniques. The program also explores real-world applications of this technology. In this program, you will:

  • Implement fundamental image processing methods and learn about various techniques used in them
  • Use neural networks to perform image recognition and classification
  • Extract 3D information from images and learn the basic principles of geometry-based vision
  • Align and track objects in a video

Program Modules

The program comprises 10 modules designed to help you leverage your Python skills and mathematical knowledge to gain deep insights into computer vision and image processing concepts.

Module 1:

Introduction to Computer Vision

The program begins by clearly defining the core concepts of computer vision and identifying real-world applications of this technology.

Module 2:

Image Processing

Explore the basic principles of image processing and learn the various techniques used for image filtering and decomposition.

Module 3:

Feature Detection and Matching

Feature detection is a cornerstone of computer vision. Explore essential feature-detection methods, and use them to build and train algorithms to detect corners and visualize quadratics in images.

Module 4:

Image Classification and Neural Networks

Leverage your experience in ML to create image representations with features using the Bag-of-Visual Words concept. Learn to use neural networks to classify images.

Module 5:

Convolutional Neural Networks (CNNs)

Learn about the structure and function of CNNs, using a deep CNN to recognize objects in an image.

Module 6:

Transformation and Homographies

Learn to apply 2D planar and linear transformations to given images, the process of performing automatic image warping, and explore basic augmented-reality simulations.

Module 7:

Camera Models

Learn the basics of geometric camera models and how to calibrate a camera.

Module 8:

Geometry-Based Vision

Discover the basic principles of geometry-based vision, learn to reconstruct 3D scene structures from 2D images, and perform robust 3D sensing using stereo.

Module 9:

Dealing With Motion

Study the applications of optical flow and track objects in a video.

Module 10:

Physics-Based Vision

Understand the function of physics-based vision in interpreting and extracting information from an image, and perform photometric stereo for rendering simple images.

Module 1:

Introduction to Computer Vision

The program begins by clearly defining the core concepts of computer vision and identifying real-world applications of this technology.

Module 6:

Transformation and Homographies

Learn to apply 2D planar and linear transformations to given images, the process of performing automatic image warping, and explore basic augmented-reality simulations.

Module 2:

Image Processing

Explore the basic principles of image processing and learn the various techniques used for image filtering and decomposition.

Module 7:

Camera Models

Learn the basics of geometric camera models and how to calibrate a camera.

Module 3:

Feature Detection and Matching

Feature detection is a cornerstone of computer vision. Explore essential feature-detection methods, and use them to build and train algorithms to detect corners and visualize quadratics in images.

Module 8:

Geometry-Based Vision

Discover the basic principles of geometry-based vision, learn to reconstruct 3D scene structures from 2D images, and perform robust 3D sensing using stereo.

Module 4:

Image Classification and Neural Networks

Leverage your experience in ML to create image representations with features using the Bag-of-Visual Words concept. Learn to use neural networks to classify images.

Module 9:

Dealing With Motion

Study the applications of optical flow and track objects in a video.

Module 5:

Convolutional Neural Networks (CNNs)

Learn about the structure and function of CNNs, using a deep CNN to recognize objects in an image.

Module 10:

Physics-Based Vision

Understand the function of physics-based vision in interpreting and extracting information from an image, and perform photometric stereo for rendering simple images.

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Program Experiences

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Office Hours With Learning Facilitators

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Programming Assignments

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Recorded Videos

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Knowledge Checks

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Dedicated Program Support Team

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Discussion Boards

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Bite-Sized Learning

Who Should Attend

This program is designed for participants who have programming experience in Python, and knowledge of multivariable calculus, linear algebra, probability, and statistics. The program is most suitable for:

Software developers/technology professionals who want to get a deep understanding of computer vision tools and advance their career with a certificate from a renowned school.

Representative roles include:

  • Software engineer
  • Software developer
  • Automation engineer
  • Tester design
  • Engineer
  • Full-stack developer
  • Tech lead

Data science/data analytics/machine learning (ML) professionals looking to improve their knowledge of computer vision technologies and their applications across industries.

Representative roles include:

  • Data scientist
  • ML engineer
  • AI application engineer
  • Data engineer
  • Senior data engineer
  • ML developer
  • ML research engineer
  • Data analyst

PREREQUISITES: This program requires a functional knowledge of linear algebra, calculus, probability, and statistics. Participants should be comfortable programming in Python. Programming assignments will present opportunities to implement computer vision algorithms using these technologies.

Faculty Members

Faculty Member Kris Kitani

Kris Kitani

Associate Research Professor, Robotics Institute, School of Computer Science Courtesy Professor, Electrical and Computer Engineering Department, Carnegie Mellon University

Kris Kitani works in the areas of computer vision, machine learning and human-computer interaction. His research interests lie at the intersection of first-person vision, human activity modeling, and inverse reinforcement learning... More info

Faculty Member Ioannis Gkioulekas

Ioannis Gkioulekas

Assistant Professor, Robotics Institute, Carnegie Mellon University

Ioannis Gkioulekas works on computational imaging — the process of forming images from measurements using algorithms that rely on a significant amount of computing. While imaging involves optics, sensors, and illumination, computation includes physics-based modeling and rendering, inverse algorithms, and learning... More info

Certificate

Certificate

Upon successful completion of the program, participants will receive a verified digital certificate of completion from Carnegie Mellon University’s School of Computer Science Executive Education. This is a training program and it is not eligible for academic credit.

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Your digital certificate will be issued in your legal name and emailed to you at no additional cost, upon completion of the program, per the stipulated requirements. All certificate images are for illustrative purposes only and may be subject to change at the discretion of Carnegie Mellon University’s School of Computer Science Executive Education.

The Carnegie Mellon School of Computer Science Executive Education learning experience

At Carnegie Mellon’s Executive Education Program in the School of Computer Science, we provide organizations and people access to the skills and tools necessary to solve real world technical problems by equipping the next generation of technology leaders with the experience, insights and novel solutions developed by our community of computer science experts. From custom training programs to online individualized learning, our cutting-edge programming — backed by faculty who pioneered the field — takes your skillset to the next level, giving you the tools to tackle your company’s next great technological challenge.

FAQs

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

    After reviewing the information on the program landing page, we recommend you submit the short form above to gain access to the program brochure, which includes more in-depth information. If you still have questions on whether this program is a good fit for you, please email learner.success@emeritus.org, and a dedicated program advisor will follow-up with you very shortly.


    Are there any prerequisites for this program?

    Some programs do have prerequisites, particularly the more technical ones. This information will be noted on the program landing page, as well as in the program brochure. If you are uncertain about program prerequisites and your capabilities, please email us at learner.success@emeritus.org for assistance.


    Note that, unless otherwise stated on the program web page, all programs are taught in English and proficiency in English is required.


    What is the typical class profile?

    More than 50 percent of our participants are from outside the United States. Class profiles vary from one cohort to the next, but, generally, our online certificates draw a highly diverse audience in terms of professional experience, industry, and geography — leading to a very rich peer learning and networking experience.


    What other dates will this program be offered in the future?

    Check back to this program web page or email us at learner.success@emeritus.org to inquire if future program dates or the timeline for future offerings have been confirmed yet.

  • How much time is required each week?

    Each program includes an estimated learner effort per week. This is referenced at the top of the program landing page under the Duration section, as well as in the program brochure, which you can obtain by submitting the short form at the top of this web page.



    How will my time be spent?

    We have designed this program to fit into your current working life as efficiently as possible. Time will be spent among a variety of activities including:



    • Engaging with recorded video lectures from faculty
    • Attending webinars and office hours, as per the specific program schedule
    • Reading or engaging with examples of core topics
    • Completing knowledge checks/quizzes and required activities
    • Engaging in moderated discussion groups with your peers
    • Completing your final project, if required

    The program is designed to be highly interactive while also allowing time for self-reflection and to demonstrate an understanding of the core topics through various active learning exercises. Please contact us at learner.success@emeritus.org if you need further clarification on program activities.



    What is it like to learn online with the learning collaborator, Emeritus?

    More than 250,000 professionals globally, across 80 countries, have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded.

    A dedicated program support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.


    How do I interact with other program participants?

    Peer learning adds substantially to the overall learning experience and is an important part of the program. You can connect and communicate with other participants through our learning platform.

  • What are the requirements to earn the certificate?

    Each program includes an estimated learner effort per week, so you can gauge what will be required before you enroll. This is referenced at the top of the program landing page under the Duration section, as well as in the program brochure, which you can obtain by submitting the short form at the top of this web page. All programs are designed to fit into your working life.

    This program is scored as a pass or no-pass ; participants must complete the required activities to pass and obtain the certificate of completion. Some programs include a final project submission or other assignments to obtain passing status. This information will be noted in the program brochure. Please contact us at learner.success@emeritus.org if you need further clarification on any specific program requirements.


    What type of certificate will I receive?

    Upon successful completion of the program, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, resume, and/or display it on your LinkedIn profile. The digital certificate will be sent approximately two weeks after the program, once grading is complete.


    Can I get the hard copy of the certificate?

    No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.


    Do I receive alumni status after completing this program?

    No, there is no alumni status granted for this program. In some cases, there are credits that count toward a higher level of certification. This information will be clearly noted in the program brochure.


    How long will I have access to the learning materials?

    You will have access to the online learning platform and all the videos and program materials for 12 months following the program start date. Access to the learning platform is restricted to registered participants per the terms of agreement.

  • What equipment or technical requirements are there for this program?

    Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts.


    Do I need to be online to access the program content?

    Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access program content from a desktop, laptop, tablet, or mobile device.

    Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you may view them later.

  • Can I still register if the registration deadline has passed?

    Yes, you can register up until seven days past the published start date of the program without missing any of the core program material or learnings.


    What is the program fee, and what forms of payment do you accept?

    The program fee is noted at the top of this program web page and usually referenced in the program brochure as well.

    • Flexible payment options are available (see details below as well as at the top of this program web page next to FEE).
    • Tuition assistance is available for participants who qualify. Please email learner.success@emeritus.org.

    What if I don’t have a credit card? Is there another method of payment accepted?

    Yes, you can do the bank remittance in the program currency via wire transfer or debit card. Please contact your program advisor, or email us at learner.success@emeritus.org for details.


    I was not able to use the discount code provided. Can you help?

    Yes! Please email us at learner.success@emeritus.org with the details of the program you are interested in, and we will assist you.


    How can I obtain an invoice for payment?

    Please email learner.success@emeritus.org with your invoicing requirements and the specific program you’re interested in enroling in.


    Is there an option to make flexible payments for this program?

    Yes, the flexible payment option allows a participant to pay the program fee in installments. This option is made available on the payment page and should be selected before submitting the payment.


    How can I obtain a W9 form?

    Please email us at learner.success@emeritus.org for assistance.

  • What is the policy on refunds and withdrawals?

    You may request a full refund within seven days of your payment or 14 days after the published start date of the program, whichever comes later. If your enrollment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to admissions@emeritus.org.



    What is the policy on deferrals?

    After the published start date of the program, you have until the midpoint of the program to request to defer to a future cohort of the same program. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrollment and are subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period, and the limit of one deferral per enrollment remains. All deferral requests should be sent to admissions@emeritus.org.

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Flexible payment options available. Learn more.