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Computer vision courses

248 Courses

California Institute of Technology University of Colorado Boulder

Deep Learning Applications for Computer Vision

Unlock the potential of your career with the "Deep Learning Applications for Computer vision" course offered by the University of Colorado Boulder on Coursera. Dive into the fascinating world of Computer Vision, and grasp both classic and cutting-edge Deep Learning methodologies. You'll explore a wide array of Computer Vision tasks such as image cl.
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provider Coursera
pricing Free Online Course (Audit)
duration 23 hours
sessions On-Demand
California Institute of Technology Columbia University

3D Reconstruction - Multiple Viewpoints

Explore the fascinating world of 3D Reconstruction from Multiple Viewpoints, a comprehensive online course offered by Columbia University through Coursera. This detailed course delves into the techniques required to recover the 3D structure of a scene utilizing images captured from various perspectives. Starting with the basics, learners will const.
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provider Coursera
pricing Free Online Course (Audit)
duration 8-9 hours
sessions On-Demand
California Institute of Technology Columbia University

3D Reconstruction - Single Viewpoint

Explore the innovative world of 3D Reconstruction from a Single Viewpoint in this comprehensive course offered by Columbia University on Coursera. Delve into the fascinating process of transforming 2D images into a 3D structure, focusing on rigid scenes captured from a stationary camera. Uncover the secrets of capturing images in such a way that ea.
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provider Coursera
pricing Free Online Course (Audit)
duration 11 hours
sessions On-Demand
California Institute of Technology Purdue University

Computer Vision for Embedded Systems

Explore the fascinating intersection of computer vision technologies like OpenCV and PyTorch with embedded systems including Raspberry Pi and Jetson in Purdue University's course offered through edX. This course delves into the challenges of deploying computer vision on resource-constrained embedded systems, introducing techniques such as quantizat.
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provider edX
pricing Free Online Course (Audit)
duration 5 weeks, 7-8 hours a week
sessions On-Demand
California Institute of Technology Waseda University

Introduction to Image Analysis for Plant Phenotyping

Explore the world of image analysis with a focus on its vital role in plant phenotyping in this comprehensive six-week course provided by the University of Nottingham and available on FutureLearn. This enlightening course is tailored to introduce you to the core concepts of image analysis and demonstrate how these techniques are applied in the real.
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provider FutureLearn
pricing Free Online Course (Audit)
duration 6 weeks, 3 hours a week
sessions On-Demand
California Institute of Technology Columbia University

Features and Boundaries

Embark on a journey with Columbia University's enlightening course offered through Coursera, titled Features and Boundaries. This meticulously designed curriculum dives deep into the essential techniques for detecting features and boundaries within images, setting the foundation for advanced vision tasks such as object detection, recognition, and p.
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provider Coursera
pricing Free Online Course (Audit)
duration 23 hours
sessions On-Demand
California Institute of Technology RMIT University

Robotic Vision

Discover the future of technological advancement with our Robotic Vision program offered by Queensland University of Technology (QUT) and available on FutureLearn. This cutting-edge series of online courses delves into the rapidly evolving field of robotic vision, a critical component in diverse sectors such as health care, marine science, and spac.
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provider FutureLearn  Program
pricing Paid Course
duration 10 weeks, 3 hours a week
California Institute of Technology Wesleyan University

Basics in computer vision

Discover the essentials of computer vision with the specialization offered by HSE University, a component of the Master of Computer Vision degree program at Wesleyan University, provided through Coursera. This specialization is designed for a broad audience, ranging from novices to professionals eager to dive into the field of Computer Vision. It's.
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provider Coursera  Specialization
pricing Paid Course
duration 13 weeks, 4 hours a week
California Institute of Technology Université de Montréal

Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality

Title: Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality Description: Dive into an immersive learning journey with the Post Graduate Certificate in Deep Learning for Computer Vision and Extended Reality, offered through a partnership between Université de Montréal and Coursera MasterTrack. This programme is meticul.
provider Coursera  MasterTrack
pricing Paid Course
duration 24 weeks, 6-8 hours a week
California Institute of Technology Udacity

Advanced Computer Vision and Deep Learning

Title: Advanced Computer Vision and Deep Learning Description: Immerse yourself in the cutting-edge realm of AI with our comprehensive course tailored to teach you the application of deep learning architectures to computer vision tasks. This course not only covers the basics but dives deeper into how Convolutional Neural Networks (CNN) and Recurren.
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provider Udacity
pricing Free Online Course
sessions On-Demand

“Computer vision student” sounds like a quote from science fiction, don’t you think? In fact, a computer vision engineer is a profession that, although it has not yet become the most widespread, is already rapidly gaining popularity and offers high salaries even at the start of a career.

What is computer vision and what does its developer do?

A computer vision engineer is a specialist who teaches computers to extract information from images. In particular, automatically recognize objects or gestures in images and videos. If a person can visually determine something (for example, find a defect in a product), a computer can also be trained to do this - and thus save time and resources, simplifying many processes.

Developments in the field of computer vision courses are used in a wide variety of companies whose products are related to images or video. This includes the production of self-driving cars, helping doctors interpret MRI images when searching for tumors, and even facial recognition in the subway to identify violators of the self-isolation regime. Computer vision specialists help many e-commerce businesses reduce the burden of moderation: for example, when an ad service like Avito fights trolls who upload pictures with inappropriate content.

Computer vision specialists after computer vision courses are called differently: developers, engineers, and researchers (computer vision scientist). Essentially, a computer vision specialist is more of an engineer who uses mathematics and programming as working tools. So, globally, a computer vision engineer, a computer vision scientist, a computer vision developer and a technical vision developer are one and the same thing.

What does a computer vision developer actually do?

As a rule, the day of such a specialist begins with a stand-up with the team. He then writes code to train neural networks, preprocesses data, and analyzes experiments. A computer vision developer can work alone or in a team, where everyone performs part of a larger task.

As for working tools, the Python language is usually used to write code for experiments, and the Tensorflow or Pytorch frameworks are used to train neural networks. The work also involves special libraries for image processing such as OpenCV. For high-load projects, the C++ language can also be used, since anything written in it is executed many times faster.

Computer vision is a young, dynamically developing field at the intersection of science and engineering, in which there are still more experiments than ready-made solutions. To grow, a specialist here needs to constantly learn. But it is the novelty and non-standard nature of the tasks, as well as the opportunity to create something truly innovative, that brings many people into this profession.

What do they teach in computer vision classes at AI Education?

Training at the best computer vision course typically consists of three modules: creating infrastructure, basics of machine learning and studying computer vision.

The first block at a computer vision online course can be called introductory. Since specialists in the field of computer vision rely on knowledge of mathematics and programming when solving problems, at the start they will have to study from scratch or brush up on topics from higher mathematics, mathematical analysis and linear algebra, as well as work with the Python language. Don’t worry if your knowledge is limited to school mathematics, which was “long ago and not true”: we will help you improve the necessary topics in the first module, so that in the future all students can move through the program at the same rhythm.

The second module is entirely devoted to machine learning. It helps solve computer vision problems faster and easier. For example, for facial recognition, you can expertly describe facial features based on questions that are asked when compiling an identikit. Or you can feed the algorithm a lot of photographic portraits with markings about which face belongs to whom, and then the algorithm itself will learn to extract features by which faces can be identified. In the future, if you need to determine who is in the photo, the algorithm will only need a database of portraits. If there is a photo of the person you need, the system itself will easily find him.

In the second module you will examine probability theory and mathematical statistics. Students will practice solving problems using fundamental algorithms and data structures in Python, become familiar with Python libraries for Data Science (NumPy, Matplotlib), as well as machine learning algorithms.

Finally, in the third module at this machine vision course you will analyze the main tasks of computer vision, we will work with mathematical morphology and the OpenCV and PIL libraries!