Best Online Computer Vision Courses

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify them. Experts say Computer vision is the next big thing in machine learning and artificial intelligence. When we are giving our machines the ability not only to analyse through data input but to see what it is, they are investigating, we open up our data to more kinds of inputs than traditional text. Neural networks that can analyse images or video are going to be the next wave of functionality for our deep learning capability.

Computer vision gives us real-time data for visual inputs. It provides an analysis of image data, including object recognition and image classification, allowing us to analyse our unstructured data more closely. Computer vision has applications in a wide range of areas from self-driving cars to smartphones. Deep learning models are making computer vision tasks more accurate, and soon, our computers will be able to see much the same way we do. It would be foolish of us to not take advantage of this growing field.

In order to do that an understanding of what makes computer vision possible is necessary. One will need to understand how computers process visual recognition and the types of convoluted neural networks that make computer vision possible. An understanding of the applications of computer vision is also crucial as they go far beyond face detection.

Let us now discuss the best courses for computer vision courses available online.

1. Become a Computer Vision Expert – Nanodegree Program by Udacity

This is a 4.5 rated course. The duration of the course is of three months. This is a nanodegree where you will get started with writing programs for analysing images, implementing feature extraction and recognizing objects using deep learning models. The pre-requisites of the course are knowledge and prior experience of Python programming language, statistics, machine learning, and deep learning. The key point for this course includes:

• Each section of this course is followed by relevant projects such as facial keypoint detection, automatic image captioning and landmark detection & tracking.
• The flexible structure of these courses allows you to learn at your own pace.
• In this program, you will get help regarding interview preparation, resume services, personal career coaching and more.
• You will get to learn techniques used in self-driving car navigation and drone flight.
• You will learn to combine CNN and RNN networks to build an application.
•  You will get to master computer vision and image processing essentials and learn to extract important features from image data and apply deep learning techniques to classification tasks.
• The course will cover topics such as Face keypoint detection, automatic image captioning, and landmark detection and tracking.

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2. Convolutional Neural Networks Course by Coursera

This is a 4.9 rated course of a short duration that is of 35 hours. This course is offered by top instructors at Coursera Andrew Ng. This course covers all the key features and concepts required to build convolutional neural networks and apply them to image data. You will get to learn to apply the networks for visual detection and recognition tasks and use neural style transfer to generate art. After completing the class, you will be ready to integrate your knowledge and work on relevant projects. The key features and points for this particular course include:

• The lectures provided with this course guides you through all the necessary topics required to handle the tools used in the lessons adequately.
• Experienced Instructors provide tips, advice and the best practices to debug and write clean codes.
• This course provides demonstrations followed by step-by-step guidance are provided to understand the concepts better.
• You will get the opportunity to work on assignments and apply the techniques covered in the classes.
• The course is divided into sections along with small assessments or questions which makes it easier to follow along.
• You will have to complete all the graded assessments and exercises in order to earn the completion certificate.
• The pre-requisites of the course are an intermediate Python skill that includes basic programming, understanding of for loops, if/else statements, data structures and a basic grasp of linear algebra & machine learning.

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3. Introduction to Computer Vision and Image Processing by Coursera

This course with a rating of 4.5 is designed by expert instructors of IBM (International Business Machines). IBM offers this course on the platform of Coursera, which makes it available to all the students around the world. This course has the ability to provide you with all the material and skills that you need to get introduced to computer vision. During the course, you will be able to communicate with your instructors if you have any queries related to the course content, or you are unable to understand the concepts in the course. The key features and points for this course include:

•  This course will provide you with several labs and exercises to help learn and understand the basic and simple concepts of computer vision
•  You will get to learn how to utilize Python, Watson AI, and OpenCV to process images and interact with image classification models
• You will get to learn how to build, train, and test your own custom images classifiers in visual recognition instance, as well as train your classifiers to classify dog images into different breeds
• You will get free access to a cloud environment that allows you to build your own computer vision web app and position it to the cloud
• This is a short course of duration 15 hours
• After successful completion of the course, you will be rewarded a certificate of completion.
• The instructors for the course are Aije Egwaikhide, a Data Scientist at IBM and Joseph Sant Arcangelo, a Ph.D., Data Scientist at IBM.

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4. Python for Computer vision with OpenCV and Deep Learning by Udemy

This program is one of the top contenders for learning how to use Python for computer vision with a rating of 4.5 out of 5. This course is a fourteen hours course commenced by learning about numerical processing and manipulating images with the NumPy library. You will get to explore the OpenCV library, process images and apply a variety of effects such as colour mapping, thresholds, gradients and more. The training will end by understanding many complex concepts, getting hands-on and discussing the latest developments. The key features of the course include:

• This course is of intermediary level and requires some knowledge and prior experience in Python.
• You get to create colour histograms with OpenCV and draw shapes on images and videos.
• You get to perform face detection, feature matching, object tracking and more.
• You get to work with a customized deep learning network, optical flow, and Watershed algorithm.
• This course provides you with 92 lectures, 4 articles and 3 downloadable resources
• You will be provided full lifetime access to the above resources.

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5. Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs by Udemy

This certification course offered by Udemy has a rating of 4.4 out of five. This course will help you have a toolbox of the most powerful Computer Vision models. This course will enhance your understanding of the theory behind Computer Vision. This course will guide you to master OpenCV, master Object Detection and master Facial Recognition. This course will make you able to create powerful Computer Vision applications. This course covers face detection intuition, face detection with Open CV, homework challenges, object detection intuition, object detection with SSD, generative adversarial networks (GANs) Intuition, image creation with GANs and Artificial Neural Networks. The key features of the course include:

• You will have a toolbox of the most powerful computer vision models.
• You will learn to master OpenCV, facial recognition and object detection.
• The instructor, Prayson Wilfred Daniel is a renowned expert in this area and explains the ideas well and at a good pace.
• You will be provided with a wide variety of examples that help you to get a clearer view of the topics.
• You will get to understand the theory behind the topics and create powerful applications.
•  You will be provided with 11 hours of on-demand video, after successful enrolment in the course.
• 13 articles and 6 downloadable resources will be provided to you, after joining the course.
• You will be provided with full-time access to the resources and you will also be given access to them on mobile and TV
• You will be rewarded with a certificate after successful completion of this course.

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6. Deep Learning: Advanced Computer Vision by Udemy

This is a certification course of rating 4.5. This course cover Machine Learning Basics, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), VGG and Transfer Learning, ResNet (and Inception), Object Detection (SSD / RetinaNet), Neural Style Transfer, Class Activation Maps, and GANs (Generative Adversarial Networks) and much more. The key features of the course are:

• With enrolment in the course, you will get 15 hours of on-demand video
• You will be provided with 2 articles
• You will gain full lifetime access
• Access on mobile and TV
• At the end of the course, you will be rewarded a Certificate of completion

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7. Python Project: Pillow, Tesseract, OpenCV by Coursera

This is a 4.0-star course offer by the University of Michigan. The instructor for the course is Christopher Brooks who is an Assistant Professor at the School of Information. The course covers The Python Imaging Library, Tesseract and Optical Character Recognition, and Computer Vision with OpenCV. The key features of the course are:

This course is a self-paced course which means the you will be able to reset deadlines in accordance to your schedule.

• The course is part of a specialization program.
• The course is not for beginners, basic knowledge in the field is a pre-requisite.
• The duration of the course is estimated to be of 20 hours.
• At the end of the course, you will be rewarded a Certificate of completion

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8. Deep Learning with Python and PyTorch by EdX

This is one of many courses of IBM offered on the platform of edx. This course covers topics including IBM’s deep learning fundamentals with Keras, PyTorch basics for machine learning, deep learning with python and PyTorch, deep learning with TensorFlow, using GPUs to scale and speed-up deep learning, applied deep learning capstone project. The key features of the course are:

• As the course is offered by a great company like IBM, the educators are expert in the field.
• This professional certification program is a composition of 6 skill-building courses
• This is a Self-paced course that lets you progress at your own speed
• The duration of the course is estimated to be of 8 months
• At the end of the course you will be rewarded a Certificate of completion

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9. Introduction to Computer Vision by Udacity

This course is a basic course on computer vision. This course covers fundamentals of image formation, camera imaging geometry, feature detection and matching, Multiview geometry including stereo, motion estimation and tracking, and classification. The key features of the course include:

• This course is a free course
• The course is not for beginners, basic knowledge in the field is a pre-requisite.
• The duration of the course is estimated to be of 4 months.
• At the end of the course, you will be rewarded a Certificate of completion

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10. Become a Computer Vision Expert by Udacity

This course is an intermediate to advanced course on computer vision offered on the platform of Udacity. This course covers introduction to computer vision, advanced level computer vision and deep learning, and object tracking and localization. The key features of the course include:

• The pre-requisite for the course includes knowledge and experience in Python, Statistics, Machine Learning, & Deep Learning
• The duration of the course is estimated to be of 3 months
• At the end of the course, you will be rewarded a Certificate of completion

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