Join

Computer vision courses

186 Courses

California Institute of Technology Coursera

AI and Disaster Management

Delve into the crucial role of AI in Disaster Management with our comprehensive course available on Coursera. This course offers an in-depth exploration of the disaster management cycle, covering all critical phases: mitigation, preparation, response, and recovery. Participants will engage with hands-on case studies to apply their learning practica.
course image
provider Coursera
pricing Free Online Course (Audit)
duration 12 hours
sessions On-Demand
California Institute of Technology Coursera

AI and Climate Change

AI and Climate Change Course Overview Dive into the pressing issue of our time with the AI and Climate Change course, available on Coursera. This educational experience begins with an essential review of anthropogenic climate change, highlighting its significant impact on global temperatures and weather patterns. As part of this course, learners wi.
course image
provider Coursera
pricing Free Online Course (Audit)
duration 15 hours
sessions On-Demand
California Institute of Technology Coursera

Object Tracking and Motion Detection with Computer Vision

Embark on a journey to master Object Tracking and Motion Detection with the final course in the Computer Vision for Engineering and Science specialization, available on Coursera. This comprehensive course is designed to equip you with the skills to track objects and detect motion across videos, a critical competency for applications ranging from mi.
course image
provider Coursera
pricing Free Online Course (Audit)
duration 14 hours
sessions On-Demand
California Institute of Technology Udemy

Convolutional Neural Networks in Python: CNN Computer Vision

Embark on a journey into the world of Computer Vision and Image Recognition with our comprehensive course on Convolutional Neural Networks (CNN) using Python. Offered through Udemy, this program is meticulously designed to leverage the capabilities of Keras and TensorFlow 2, ensuring participants gain hands-on experience with the latest technologie.
course image
provider Udemy
pricing Paid Course
duration 7 hours 48 minutes
sessions On-Demand
California Institute of Technology Coursera

Computer Vision with Embedded Machine Learning

Embark on a journey into the fascinating world of Computer Vision (CV) with our cutting-edge course designed to equip you with the skills to enable computers to perceive and interpret the world. This course, a collaborative effort by Edge Impulse, OpenMV, Seeed Studio, and the TinyML Foundation, dives deep into how deep learning and neural networks.
course image
provider Coursera
pricing Free Online Course (Audit)
duration 31 hours
sessions On-Demand
California Institute of Technology Independent

Seeing Clearly: Computer Vision Theory

Delve into the fascinating world of computer vision with our comprehensive courses. Learn how machines interpret images and videos, mastering topics such as the automatic recognition of objects and activities. Discover the groundbreaking technology behind the world's first deep learning-enabled camera. Through engaging demonstrations, gain insights.
provider Independent
pricing Free Online Course
duration 2-3 hours
sessions On-Demand
California Institute of Technology edX

Computer Vision and Image Processing Fundamentals

Please Note: Completing this IBM course successfully gives you the opportunity to earn a skill badge — a sophisticated, verifiable, and digital credential outlining the knowledge and abilities you've gained. Enroll, complete the course, and claim your badge to learn more! Computer Vision stands at the forefront of the most thrilling domains in Mach.
course image
provider edX
pricing Free Online Course (Audit)
duration 3 weeks, 3-4 hours a week
sessions On-Demand
California Institute of Technology Coursera

Advanced Computer Vision with TensorFlow

Embark on a transformative journey with the "Advanced Computer Vision with TensorFlow" course, available on Coursera and crafted by DeepLearning.AI. This comprehensive specialization is designed for early to mid-career software and machine learning engineers who have a foundational grasp of TensorFlow and are eager to broaden their expertise with i.
course image
provider Coursera
pricing Free Online Course (Audit)
duration 19 hours
sessions On-Demand
California Institute of Technology Udacity

Intel® Edge AI Fundamentals with OpenVINO™

Discover the forefront of AI technology through the "Intel® Edge AI Fundamentals with OpenVINO™" course offered by Udacity. This specialized training empowers you to harness the power of edge computing by deploying advanced edge AI capabilities. Master the Intel® Distribution of the OpenVINO™ toolkit, a critical resource for developing efficient co.
provider Udacity
pricing Free Online Course
duration 4 weeks
sessions On-Demand
California Institute of Technology Coursera

Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications

Welcome to our course on "Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications", offered through Coursera. This program is your gateway to mastering the foundational elements of the Intel Distribution of OpenVINO toolkit. Engage in a series of demos to explore the impressive capabilities and tools this toolkit e.
course image
provider Coursera
pricing Free Online Course (Audit)
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!