Computer vision courses

316 Courses

Udemy

Ollama Zero to Hero: Build Chat, Vision Games & AI Agents

Ollama Zero to Hero: Build Chat, Vision Games & AI Agents Join the transformative journey from an AI novice to an expert with the "Ollama Zero to Hero: Build Chat, Vision Games & AI Agents" course. Dive into mastering Local LLMs through the creation of four distinct AI projects with Python, progressing from basic chat applications to sophisticate.

Udemy

Motion Detection using Python and OpenCV

Course Title: Motion Detection using Python and OpenCV Course Overview: Learn how to implement a vehicle counter and social distancing detector using advanced background subtraction algorithms. This course offers a comprehensive, step-by-step guide to mastering these essential computer vision techniques with Python and OpenCV. Provider: Udemy Un.

CourseHorse

Designing and Implementing an Azure AI Solution (Live Online)

Participate in our interactive online course, "Designing and Implementing an Azure AI Solution," where you'll develop a sophisticated customer support Chat Bot using artificial intelligence from the Microsoft Azure platform. Gain expertise in language understanding and leverage pre-built AI functionalities available in Azure Cognitive Services.

Coursera

Data Science & Inteligencia Artificial aplicados a negocios

Explora el poder transformador de la inteligencia artificial y la ciencia de datos en el entorno empresarial moderno con nuestro curso especializado. Descubre la aplicación práctica de estas tecnologías para mejorar la toma de decisiones y afrontar retos complejos de manera ética y efectiva. A medida que la IA redefine el mundo corporativo.

LinkedIn Learning

Microsoft Azure AI Essentials Professional Certificate by Microsoft and LinkedIn

Embark on a transformative learning journey with the Microsoft Azure AI Essentials Professional Certificate offered by Microsoft and LinkedIn. This course is designed for tech professionals and business leaders eager to delve into machine learning and AI fundamentals, along with Microsoft Azure's related services. Throughout the course, you.

LinkedIn Learning

Künstliche Intelligenz (KI) – Grundlagen

Vertiefen Sie Ihr Wissen über Künstliche Intelligenz (KI) und Machine Learning (ML) durch einen detaillierten Überblick über deren Geschichte, Techniken und Einsatzbereiche. Dieser Kurs von LinkedIn Learning bietet umfassende Einblicke und Anleitungen für alle Interessierten im Bereich der entwickelnden Technologie, einschließlich Computer Vis.

DataCamp

Image Processing in Python

Delve into the world of image processing, an essential aspect of data science. This comprehensive track by DataCamp introduces you to the core techniques used in handling images, starting from basic image enhancements to sophisticated restoration strategies. As you progress, you will explore the intricacies of biomedical imagery, learning to.

Udemy

Mastering OpenCV: A Practical Guide to Computer Vision

Delve into the fascinating world of computer vision with our comprehensive course, "Mastering OpenCV: A Practical Guide to Computer Vision" offered by Udemy. This course is meticulously designed to equip you with skills in image manipulations, video processing, and object detection, using the powerful OpenCV library. Whether you're a beginner.

CourseHorse

AI Generative Imaging: Introduction to Image Making (Live Online)

University of Michigan

AI for Autonomous Vehicles and Robotics

Immerse yourself in the transformative world where artificial intelligence meets autonomy in the course: AI for Autonomous Vehicles and Robotics. Offered by the University of Michigan, this course on Coursera provides a comprehensive journey into how machine learning algorithms are redefining autonomous systems. Explore the depths of supervis.

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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!