Computer vision courses

316 Courses

AI-900: Microsoft Certified: Azure AI Fundamentals -Dec 2024

Get ready to pass the AI-900: Microsoft Certified Azure AI Fundamentals exam with ease. This comprehensive course on Udemy guides you through essential AI concepts, tailored for both beginners and professionals eager to master Azure AI. Simplify your learning journey by completing the entire course in just one day. The course includes compl.
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Python Zero to Hero: Master Coding with Real Projects

Unlock the power of Python with the Python Zero to Hero: Master Coding with Real Projects course offered by Udemy. Whether you're a beginner or looking to deepen your skills, this course is tailored to guide you through the essentials and beyond, utilizing hands-on projects that teach you coding in a practical and engaging way. What You Will Lea.
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Self-Driving Car Specialization Course

Embark on a transformative journey into the cutting-edge world of self-driving cars through this comprehensive specialization. This course covers foundational principles and advanced decision-making required to design, implement, and test self-driving car technologies. The curriculum begins with an introduction to autonomous vehicles, detailin.
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Microsoft Applied Skills: Build an Azure AI Vision solution

Unlock the power of Azure AI Vision with our comprehensive course, Microsoft Applied Skills: Build an Azure AI Vision Solution, available exclusively on Udemy. This course, coded APL-3004, is your gateway to mastering image analysis by learning how to analyze images and develop custom image analysis models effectively. Perfect for those int.
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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.
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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.
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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.
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Learn Google's Gemini and Anthropic's Claude API with Python

Explore the world of advanced artificial intelligence with our comprehensive course on Udemy, "Learn Google's Gemini and Anthropic's Claude API with Python." This course is designed to empower you with the skills to develop groundbreaking applications using the powerful Google Gemini 1.5 and Anthropic Claude 3 large language models (LLMs). Th.
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PyTorch for Deep Learning Bootcamp: Zero to Mastery

Elevate your understanding of Deep Learning with the PyTorch for Deep Learning Bootcamp: Zero to Mastery. Offered by Udemy, this comprehensive course is designed for individuals eager to dive into the world of Machine Learning using the powerful PyTorch library developed by Facebook. Gain hands-on experience with practical examples that cover.
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“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!