Computer vision courses

309 Courses

Udemy

Artificial Intelligence for Finance, Accounting & Auditing

Explore the Course on Udemy Immerse yourself in the world of artificial intelligence with our comprehensive course designed specifically for professionals in finance, accounting, and auditing. This beginner-level course offers a hands-on approach to learning eight cutting-edge AI techniques without any coding prerequisites. Perfectly tail.

Udemy

TensorFlow Hub: Deep Learning, Computer Vision and NLP

Join the TensorFlow Hub course to effortlessly develop projects in the rapidly growing fields of computer vision and natural language processing. This course, provided by Udemy, empowers you to create innovative solutions with just a few lines of code. Gain expertise in various key areas, including: Computer Vision Deep Learning Neura.

Udemy

Become a TensorFlow Certified Professional Developer

Elevate your AI expertise with our immersive training program designed to prepare you as a TensorFlow Certified Developer. Offered by Udemy, this course provides an unparalleled opportunity to sharpen your skills in various key AI domains. Whether you're delving into Machine Learning, diving deep into Neural Networks, or exploring the intricac.

Udemy

Introduction to Augment Reality AR

Discover the intriguing world of Augmented Reality (AR) and start experimenting right from your living room. This introductory course offered by Udemy will guide you in how to utilize items you already own to dive deeper into AR technology. Perfect for enthusiasts eager to explore computer vision, virtual reality, and 3D modeling, this course.

Udemy

Data Science & Machine Learning: Naive Bayes in Python

Join the "Data Science & Machine Learning: Naive Bayes in Python" course on Udemy and elevate your understanding of a fundamental AI algorithm. This course is designed to significantly boost your Python programming prowess. This comprehensive program covers the Naive Bayes algorithm, a key technique in data classification and probability theo.

Udemy

Intelligently Extract Text & Data from Document with OCR NER

Enhance your skills by participating in the Document Scanner App project focused on intelligently extracting text and data through OCR and NER technologies. Dive deep into the technical realm with OpenCV, Pytesseract, and Spacy to refine your abilities in extracting named entities from scanned documents. Offered by Udemy, this comprehensive co.

Udemy

AI-900 Course Azure AI Fundamentals with Virtual Simulations

Udemy

Generative Adversarial Networks (GANs): Complete Guide

Embark on a journey into the innovative world of Generative Adversarial Networks (GANs) with our complete guide. This course offers an in-depth exploration of deep learning and computer vision, empowering you to implement transformative projects utilizing GANs, a pivotal technology reshaping the digital landscape. Offered by Udemy, this course.

Udemy

Artificial Intelligence and Machine Learning: Complete Guide

Artificial Intelligence and Machine Learning: Complete Guide Are you eager to dive into the world of Artificial Intelligence but unsure where to begin? Our comprehensive guide is designed just for you. You will learn everything you need to know in both theory and practical application. Offered by Udemy, this course covers a wide range of catego.

Udemy

Azure AI-050: Generative AI Solutions with Azure OpenAI

Join the Azure AI-050 course to swiftly learn to build Generative AI solutions with the Azure OpenAI Service. This engaging course by Udemy combines the power of Azure and Artificial Intelligence, offering a comprehensive understanding of integrating Generative AI technologies through a series of meticulously designed modules. Designed for t.

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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!