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Computer vision courses

248 Courses

California Institute of Technology Udemy

Automated Machine Learning for Beginners (Google & Apple)

Automated Machine Learning for Beginners (Google & Apple) Embark on your journey to mastering AI with our comprehensive beginner's course on Automated Machine Learning, offered via Udemy. This meticulously designed course caters to enthusiasts eager to delve into AI aspects like Computer Vision, Natural Language Processing (NLP), and handling Tabul.
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provider Udemy
pricing Paid Course
duration 3 hours 35 minutes
sessions On-Demand
California Institute of Technology Udemy

AI-900 Microsoft Azure AI Fundamentals Certification

AI-900 Microsoft Azure AI Fundamentals Certification Preparation Course Explore the realms of artificial intelligence with the AI-900 Microsoft Azure AI Fundamentals Preparation Course, offered by Udemy. This course is specifically designed to help learners prepare for the AI-900 Microsoft Azure AI Fundamentals Certification. Covering crucial topic.
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provider Udemy
pricing Paid Course
duration 4 hours 35 minutes
sessions On-Demand
California Institute of Technology AWS Skill Builder

Computer Vision with GluonCV

Computer Vision with GluonCV In this course, you will build a useful understanding of the components of a convolutional neural network (CNN) like convolutions and pooling layers, etc. In this course, Alex Smola and Tong He show how to implement some computer vision techniques using GluonCV, a computer vision toolkit. Intended Audience This cour.
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provider AWS Skill Builder
pricing Free Certificate
duration 2 hours
sessions On-Demand
California Institute of Technology AWS Skill Builder

Visión artificial con GluonCV (Español Latinoamérica) | Computer Vision with GluonCV (Spanish from Latin America)

Visión artificial con GluonCV (Español Latinoamérica) | Computer Vision with GluonCV (Spanish from Latin America) Nota: Este curso caducará el 29/11/2023. Si desea completarlo, hágalo antes de esa fecha. No hay ningún curso de reemplazo en este momento. Descripción: En este curso, obtendrá conocimientos útiles sobre los componentes de una red ne.
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provider AWS Skill Builder
pricing Free Certificate
duration 2 hours
sessions On-Demand
California Institute of Technology openHPI

Praktische Einführung in Deep Learning für Computer Vision

Praktische Einführung in Deep Learning für Computer Vision Über “Neuronale Netze”, “Artificial Intelligence” und “Deep Learning” reden heute alle. Jeder möchte künstliche Intelligenz nutzen, doch wie fange ich am besten damit an? In diesem Kurs werden wir künstliche neuronale Netze, die Grundlage künstlicher Intelligenz, sowohl theoretisch als auch.
provider openHPI
pricing Free Online Course
duration 4 weeks
sessions On-Demand
California Institute of Technology OpenClassrooms

Classez et segmentez des données visuelles

Classez et segmentez des données visuelles Bienvenue dans le cours de vision par ordinateur ! Dans ce cours, vous allez apprendre à classifier des images à l'aide des algorithmes issus du Machine Learning, en particulier de l'apprentissage supervisé (approche plutôt traditionnelle) et du Deep Learning (approche très moderne). La première partie vo.
provider OpenClassrooms
pricing Free Online Course
duration 15 hours
sessions On-Demand
California Institute of Technology Coursera

Neuronale Netze und Deep Learning

Wenn auch Sie topaktuelle KI für sich nutzen möchten, sind Sie mit diesem Kurs auf dem richtigen Weg. Deep Learning-Pioniere sind vielgefragt und wenn Sie Deep Learning einmal gemeistert haben, stehen Ihnen zahlreiche Karrieremöglichkeiten offen. Deep Learning ist eine neue „Superkraft“, mit der Sie KI-Systeme entwickeln können, die so vor ein.
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provider Coursera
pricing Free Online Course (Audit)
duration 20 hours
sessions On-Demand
California Institute of Technology Coursera

Réseaux neuronaux convolutifs

Réseaux neuronaux convolutifs Ce cours vous apprendra à créer des réseaux neuronaux convolutifs et à les appliquer aux données d’image. Grâce à l’apprentissage en profondeur, la vision par ordinateur fonctionne beaucoup mieux qu’il y a seulement deux ans, ce qui permet de nombreuses applications passionnantes allant de la conduite autonome en to.
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provider Coursera
pricing Free Online Course (Audit)
duration 20 hours
sessions On-Demand
California Institute of Technology Udemy

【Pythonで学ぶ】OpenCVでの画像処理入門

【Pythonで学ぶ】OpenCVでの画像処理入門 【Pythonで学ぶ】OpenCVでの画像処理入門 OpenCVの導入・画像の基礎知識からエッジの検出・特徴抽出、特徴追跡など様々な画像処理を紹介。実践力強化のため、パーティクルフィルターも原理を理解した後、自力で実装します。 大学: Udemy 提供 カテゴリ: Python Courses, Computer Vision Courses, OpenCV Courses
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provider Udemy
pricing Paid Course
duration 5 hours 58 minutes
sessions On-Demand
California Institute of Technology Udemy

OpenCV. Curso de OpenCV para visión por ordenador con Python

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provider Udemy
pricing Paid Course
duration 3-4 hours
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!