Computer vision courses

248 Courses

Udacity

AWS Machine Learning Engineer Nanodegree

AWS Machine Learning Engineer Nanodegree AWS Machine Learning Engineer Nanodegree The AWS Machine Learning Engineer (MLE) Nanodegree program aims to empower software developers and data scientists with essential data science and machine learning skills. This program emphasizes the construction and deployment of machine learning.

France Université Numerique

L'intelligence artificielle générative et moi

L'intelligence artificielle générative et moi Voici un mini MOOC pour vous former rapidement à l’IA générative dans votre quotidien. Il s’agira de comprendre comment elle transforme notre vie de tous les jours, nos métiers et nos compétences. Université: France Université Numerique Catégories: Cours d'Intelligence Artificielle, Cours de Machine.

PyTorch for Deep Learning

PyTorch for Deep Learning Learn PyTorch and become a proficient Deep Learning Engineer. This PyTorch course is a step-by-step guide designed to help you develop your own deep learning models. The curriculum includes essential topics such as Computer Vision, Neural Networks, and much more.

LinkedIn Learning

OpenAI API: Image Generation with DALL-E

OpenAI API: Image Generation with DALL-E | LinkedIn Learning Discover the fundamentals and advanced techniques of DALL-E in this intermediate-level course focused on AI-powered image generation. Offered by LinkedIn Learning, this course provides an in-depth exploration of DALL-E's features and capabilities. Perfect for those interested.

LinkedIn Learning

Using AI for UX Design and Research

Using AI for UX Design and Research Explore the many ways in which UX designers and researchers can ethically and inclusively leverage AI in their workflows.

openSAP

Building AI and Sustainability Solutions on SAP BTP

Building AI and Sustainability Solutions on SAP BTP This course explores how SAP is taking action on sustainability goals and enabling customers to become intelligent, sustainable enterprises. SAP Business Technology Platform provides a foundation for application development, integration, data, analytics, and AI. SAP has also developed a sustain.

LinkedIn Learning

Prepare for the Microsoft Azure AI Fundamentals (AI-900) Certification

Prepare for the Microsoft Azure AI Fundamentals (AI-900) Certification The Azure AI Fundamentals exam measures your understanding of AI fundamentals, Azure AI services, machine learning models, data preparation and processing, and best practices for AI. The courses in this learning path align with these topics to provide comprehensive preparation.

Pluralsight

Microsoft Certified: Azure Azure AI Engineer Associate (AI-102): Exam Preparation

The AI-102 certification exam tests your ability to build, manage, and deploy AI solutions using Azure AI. This course equips you with the knowledge needed to tackle the exam confidently. Are you ready to take on the Microsoft Azure AI Engineer Associate Exam? In the course titled "Microsoft Certified: Azure AI Engineer Associate (AI-102): Exam.

XuetangX

AI TIME CVPR 专场五

AI TIME CVPR 专场五 - Cutting-edge Computer Vision and AI Conference Join the AI TIME CVPR 专场五, a Chinese-language session focused on the latest advancements in computer vision and artificial intelligence. This event marks the fifth installment of the prestigious AI TIME CVPR series, where experts gather to share insights and propel the fi.

XuetangX

AI TIME CVPR 专场二

AI TIME CVPR 专场二 - XuetangX Delve into the forefront of computer vision and artificial intelligence with the AI TIME CVPR 专场二, the second session in this special series. Conducted in Chinese, this conference session presents an excellent opportunity to engage with expert presentations and cutting-edge discussions, propelling your underst.

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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!