The demand for undertaking a career in AI and computer vision is greater now than ever and just like anything else in the digital world, you can gain in-depth knowledge all about it online. Many people tend to underestimate the quality associated with online courses compared to offline studies, college-level programs, or even practical knowledge in the field.
However, online learning has developed far past that misconception, and the internet has evolved into a hub for professional-grade courses offered by specialists in the field, industry-leading companies, and noteworthy educational institutions. You can easily find a selection of paid and online courses that cover anything from the basics of computer vision down to specific elements. Whether you want to start a new career as a computer vision engineer (and associated career paths) or develop your already existing skills in 2022, you’ll certainly find something in the list we’ve compiled of some of the best computer vision courses available now.
Know exactly what you’re looking for? Navigate to any one of our specific course suggestions from the list below:
- Computer vision courses for beginners
- Intermediate level computer vision courses
- Advanced computer vision courses
- Best free, online courses
Computer vision courses for beginners
Navigating the world of computer vision is difficult for newcomers in the industry, especially if you do not have any prior experience in related fields of study. For that reason, even in introductory computer vision courses, it’s recommended that you enroll only after acquiring background knowledge in statistics, linear algebra, probability, and calculus. It’s also heavily recommended to have practical skills with a programming language or a computing environment like Python or MATLAB to be able to execute projects with them as you learn. If you have preliminary knowledge of all of the above-mentioned, let’s take a look at some beginner computer vision courses for you to consider that are just challenging enough as you need them to be for an effective introduction to computer vision.
Computer vision basics
Don’t miss out on this Coursera course offered by the joint effort of the University at Buffalo and the State University of New York. It can also double as a refresher for those who already have learned about computer vision and want to brush up on their knowledge. Just as the name suggests, this course will cover the essential components of AI and computer vision, including topics such as light formation, image formation, different levels of vision, digital signal processing, and more. The recommended preliminary requirements for this course in order to get the most out of it are basic knowledge of MATLAB, linear algebra, calculus, and random variables. When you enroll in the course, you will also be provided with free access to MATLAB for the entire duration of the course to participate in related assignments.
Fee: Free audit, $49 for full course with certification
Certification: Provided with purchase and completion of the full course
Duration: ~13 hours
Computer vision masterclass
For beginners who want to learn computer vision, it’s best to acquire a little bit of knowledge on everything before diving deeper into specific branches and components. The Computer Vision Masterclass course offered via Udemy is a favorite among beginners since it provides coverage of many areas of computer vision with few prerequisites needed. All you are required to know according to the course creators is basic programming logic and familiarity with Python. Skills you will learn through this course include but are not limited to the basic understanding of detecting faces, implementing image segmentation, extracting pixels and features from visuals, and detecting objects with OpenCV.
Fee: $199
Certification: Provided upon completion
Duration: ~25 hours content provided
Deep learning and computer vision A-Z™: OpenCV, SSD & GANs
If you’re looking for a well-rounded course that covers anything from object detection to facial recognition, utilization of OpenCV, complete theory of computer vision and its applications, then this joint-lectured course is available on Udemy. This computer vision course is ideal for beginners with minimal experience in the industry as only basic knowledge of Python and mathematics are required, according to the course creators.
Fee: $199
Certification: Provided upon completion
Duration: 11 hours content provided
Intermediate level computer vision courses
After you have a stable foundation in computer vision, it’s time to expand on the general knowledge by understanding more specific processes. For example, deciding whether you want to learn more about machine learning or deep learning at the moment, specifics such as semantic segmentation, and so on. Let’s look at a couple of intermediate-level computer vision courses to consider enrolling in.
Supervised machine learning: Classification from IBM
At the intermediate level, it is best to dive deeper than merely the basics of computer vision and into the specifics. If you want to pursue a career primarily in supervised machine learning, then this course from IBM on Coursera is worth taking a look at. IBM offers several courses on Coursera covering a wide range of computer vision topics. This one specifically concentrates on teaching different models and applications of classification, including how to work with unbalanced datasets. The recommended prerequisites for this course are familiarity with Python, data cleaning, probability, statistics, and exploratory data analysis.
Fee: $49/month (financial aid available)
Certification: Provided
Duration: ~11 hours
Python for computer vision with OpenCV and deep learning
Know Python and want to begin utilizing it along with OpenCV? Then we can’t think of a computer vision course with this concentration other than the one offered by Jose Portilla on Udemy with a 4.6-star rating out of 38,000+ students. The course begins with OpenCV basics and gradually develops into more difficult projects. You will gain practical experience from this Python/OpenCV course for tracking objects in video content, detecting objects with associated techniques (edge, corner, & grid detection), building classifiers with deep learning, and more.
Fee: $199
Certification: Provided upon completion
Duration: ~14 hours content provided
Convolutional neural networks by Coursera
To become more familiar with computer vision applications, such as facial recognition, reading radiology images, and to learn to build your own convolutional neural network (CNN), check out Coursera’s hot offering. Taught by the legend himself, Andrew Ng, the course is the fourth one in the series of Deep Learning Specialization lectures. It teaches how to solve multi-class image classification problems by focusing on edge detection, padding, strided convolutions, pooling layers, CNN examples, and more. The entire deep learning series also covers facial recognition systems, Tensorflow, object detection, and segmentation.
Fee: $49/month (financial aid available)
Certification: Provided upon completion
Duration of CNN only: ~4 weeks
Advanced computer vision courses
At this point, you’re serious about a career in computer vision and willing to invest more time — and possibly resources — to acquire in-depth knowledge. We’ve searched and found a couple of the best advanced computer vision courses that you can enroll in for 2022 to strengthen your grasp on the subject even more.
Become a computer vision expert — Nanodegree
If you want to launch your entrance into the industry as a computer vision engineer, this computer vision nanodegree offered by Nvidia will certainly put you several steps closer. Keep in mind that this is an advanced computer vision course and will provide you with an extensive understanding of data labeling, image captioning, object tracking, neural network architectures, object recognition, and more. Prerequisites for this course include: intermediate to advanced Python experience, familiarity with object-oriented programming, intermediate level statistics background, intermediate knowledge of machine learning techniques, prior experience with a deep learning framework like TensorFlow, Keras, or PyTorch.
Fee: $1017 at once or monthly $399 for 3 months
Certification: Provided
Duration: 3 months (15 hours/week)
Machine learning with Python: From linear models to deep learning
Want to do an advanced course but don’t have the time for it just now? Lucky for you that this advanced computer vision course associated with the MITx MicroMasters program begins in May 2022. According to the syllabus, you will learn regression, clustering, and classification in machine learning along with neural networks and kernel machines upon completion of this 15-week course. You will be able to entirely implement, train, and organize machine learning projects. Prerequisite knowledge for the course includes proficient Python programming skills, college-level calculus (multi-variable), vectors and matrices, and a completed course on probability theory.
Fee: Free (upgrade available)
Certification: Provided with the upgraded version
Duration: 15 weeks
Best free, online courses
What if we told you there are perfectly informative and well-structured courses out in the world that are completely free of charge? Let’s take a look at how to learn computer vision on a budget without compensating for quality.
Introduction to computer vision from Udacity
This next one is a fundamentals course on computer vision that is still a bit more challenging than a full beginner’s course. You can expect to gain a balance of theoretical and practical skills at the end of this course regarding image processing, feature detection, recognition and classification, image motion, and more. Although you do not need any previous knowledge of vision specifically to take this course, prerequisites include understanding of data structures, experience with either MATLAB or Python with NumPy, vector calculus, and algebra.
Fee: free
Certification: Provided
Duration: ~4 months
Computer vision and image processing fundamentals
The Computer Vision and Image Processing Fundamentals course is yet another incredible course offered by IBM on edx. Access to the learning materials of the entire course is free of charge, however, it will require an upgrade if you want to receive a shareable certificate. Nonetheless, it is an exemplary introductory course in computer vision fundamentals, including image processing, computer vision applications, Python and OpenCV utilization, and building image classifiers. This is a fully introductory course according to the course creators and you do not need to fulfill any prerequisites before enrolling.
Fee: free ($99 upgrade available)
Certification: Provided with the upgraded version
Duration: ~3 weeks
Start your 2022 off right by developing existing skills or undertaking an entirely new career path in the computer vision industry.
