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Computer vision courses

326 Courses

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California Institute of Technology Coursera

Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications

Welcome to our course on "Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications", offered through Coursera. This program is your gateway to mastering the foundational elements of the Intel Distribution of OpenVINO toolkit. Engage in a series of demos to explore the impressive capabilities and tools this toolkit e.
provider Coursera
sessions On-Demand
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California Institute of Technology Coursera

Emotion AI: Facial Key-points Detection

Embark on a captivating journey into the world of AI with our project-based course, "Emotion AI: Facial Key-points Detection". This comprehensive 1-hour course is designed for individuals eager to dive deep into the fascinating realms of Deep Learning, Convolutional Neural Networks (CNNs), and Residual Neural Networks. Offered on Coursera, this cou.
provider Coursera
sessions On-Demand
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California Institute of Technology Coursera

Explainable AI: Scene Classification and GradCam Visualization

Join us for a meticulously crafted 2-hour, hands-on project on Explainable AI: Scene Classification and GradCam Visualization, presented by Coursera. This immersive experience will take you through the process of training a cutting-edge deep learning model capable of identifying various types of scenery in images. Beyond mere classification, this p.
provider Coursera
sessions On-Demand
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California Institute of Technology Coursera

AutoML for Computer Vision with Microsoft Custom Vision

Embark on a thrilling journey into the world of Automated Machine Learning (AutoML) with our hands-on project on AutoML for Computer Vision, proudly offered through Coursera. This cutting-edge project introduces you to the powerful capabilities of Microsoft's Custom Vision service, a user-friendly tool that empowers you to teach computers to differ.
provider Coursera
sessions On-Demand
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California Institute of Technology Microsoft Learn

Microsoft Azure AI Fundamentals: AI Overview

Title: Microsoft Azure AI Fundamentals: AI Overview Description: Embark on a foundational journey with the Microsoft Azure AI Fundamentals course. Gear up for an in-depth exploration starting with Module 1: Get started with AI on Azure. This initial module sets the stage by unveiling the myriad of solutions AI empowers users with, alongside emphasi.
provider Microsoft Learn
sessions On-Demand
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California Institute of Technology Skillshare

Self-Driving Cars Tutorial: Identify Lane Lines with OpenCV & Python

In this engaging tutorial, explore the fascinating world of self-driving cars as you master the art of identifying lane lines using OpenCV and Python. This comprehensive lesson is meticulously designed for learners at any stage, providing a deep dive into the intriguing realm of computer vision techniques. Self-driving cars represent a monumental l.
provider Skillshare
sessions On-Demand
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California Institute of Technology Udemy

Computer Vision with OpenCV Python | Official OpenCV Course

```html Embark on your journey into the realm of Computer Vision with the Official OpenCV Course, now available on Udemy. Dive into the expansive world of OpenCV, the premier library for Computer Vision that stands as the most comprehensive of its kind globally. This course is designed to introduce you to the foundational concepts and applications.
provider Udemy
sessions On-Demand
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California Institute of Technology Microsoft Learn

Microsoft Azure AI Fundamentals: Computer Vision

Title: Microsoft Azure AI Fundamentals: Computer Vision. Description: This comprehensive course offered by Microsoft Learn covers various modules designed to give participants deep insights into the application of AI in computer vision. Key modules include:Analyzing images with the Computer Vision service, where participants learn how to leverage t.
provider Microsoft Learn
sessions On-Demand
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California Institute of Technology Microsoft Learn

Extract text from images and documents

Title: Extract Text from Images and Documents Description: Dive into the world of image and document analysis with our comprehensive course, offered by Microsoft Learn. This course is designed to equip you with the skills to leverage Azure's cutting-edge Computer Vision services. Transform the way you process visual data by mastering the use of Azu.
provider Microsoft Learn
sessions On-Demand
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California Institute of Technology Udemy

Python for Computer Vision with OpenCV and Deep Learning

Discover cutting-edge strategies in computer vision utilizing Python, OpenCV, and Deep Learning with our comprehensive course provided by Udemy. This tutorial is essential for those looking to stay ahead in fields such as Python programming, computer vision, deep learning, and more, including specialization in NumPy, OpenCV, image segmentation, and.
provider Udemy
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!