Learn Computer Vision

Computer vision (also called machine vision) is one of the most exciting frontiers in computing. With computer vision, anyone with the right skills can solve problems that used to take years of research to solve. You can build a model to detect defects in products, to identify wildfires, or to detect the wildlife in a given area. If a solution benefits from identifying or tracking objects in video or finding objects in an image, computer vision can be helpful.

Here, we have curated our best free learning resources into a Roboflow Computer Vision Course to help you start learning computer vision.

Computer vision foundations

Before you begin building your first model, you first need to learn the fundamentals of computer vision. In this section, we list tutorials and guides that discuss what computer vision is, what classes of problems can be solved with computer vision, and what the process looks like to build a successful computer vision model. The knowledge you acquire in this section will set you in good stead to solve your first model with computer vision.

Expand your knowledge

In this section, we have aggregated tutorials that will be useful as you begin training your first model. We answer common questions like "What is Mean Average Precision?" and provide key knowledge about how to use preprocessing and augmentation to build a more accurate model. We also have resources on evaluating models so you'll know the metrics that reflect the performance of your model.

Learn how to deploy computer vision models

Once you have built a model, the next task is to deploy it into production for use in the real world. In this section, we have aggregated tutorials for deploying computer vision models, providing you with the resources you need to start using your models. You can deploy models across many devices, from "edge deployment" cameras like the Luxonis OAK all the way to your browser.


Computer vision has use cases across dozens of industries. For example, construction sites can use computer vision to prevent accidents by detecting when people are too close to moving vehicles. Manufacturers of parts for cars can use computer vision to identify defects in products when they are on the assembly line. But, you may be wondering: what small and practical projects can I build to test my skills?

Below, we have curated some of our favorite tutorials on projects you can build with computer vision at home. However, do not let the ideas in the section below limit you. If you have a project idea that could benefit from being able to identify objects in an image or a video, you will be able to use your computer vision skills! There's no better way to reinforce what you have learned about computer vision than to build your own project that solves a problem you have.

Frequently Asked Questions

Is it hard to learn computer vision?

With software like Roboflow, you can build a computer vision model without any prior computer vision experience. Previously, learning computer vision involved an extensive investment of time and computing resources. Over the last few years, there have been advances in the field to make the technology more approachable. Now, you can use tools like Roboflow to build models hands-on without minimal to no code, which makes the learning process easier.

Learning hands-on computer vision with code is more difficult, however, often involving months of learning. This is an appropriate to take in your learning if you want to understand the "how" behind modern computer vision algorithms and build model architectures, infrastructure, or configurations from scratch.

How long does it take to learn computer vision?

You can build a computer vision algorithm in about a day with a tool like Roboflow, which handles the technical back-end and empowers you to focus more on solving a particular problem with computer vision. It takes a few days to learn about the different types of problems you can solve with computer vision and a few weeks to learn more fundamentals like improving model performance and deployment.

If you want to become a computer vision engineer, expect to spend a few months learning computer vision algorithm fundamentals, assuming you already have some prior knowledge of software engineering and mathematics. Your learning will involve learning about the structure of modern architectures, the evolution of computer vision, and the "how" and "why" behind today's state-of-the-art systems. Practical experience building models, optionally in a structured course or degree, will go a long way to help you building knowledge, too. You can expect to spend about a year building a solid foundation of the skills you'd need to start working on computer vision models for a business.

Continue your learning

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