Introduction to Computer Vision and Image Processing from Coursera

Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such as self-driving cars, robotics, augmented reality, and much more. In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries.

As part of this course, you will utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection.

This is a hands-on course and involves several labs and exercises. Labs will combine Jupyter Labs and Computer Vision Learning Studio (CV Studio), a free learning tool for computer vision. CV Studio allows you to upload, train, and test your own custom image classifier and detection models. At the end of the course, you will create your own computer vision web app and deploy it to the Cloud.

This course does not require any prior Machine Learning or Computer Vision experience. However, some knowledge of the Python programming language and high school math is necessary.

What's inside

Syllabus

Introduction to Computer Vision

In this module, we will discuss the rapidly developing field of image processing. In addition to being the first step in Computer Vision, it has broad applications ranging anywhere from making your smartphone's image look crystal clear to helping doctors cure diseases.

Image Processing with OpenCV and Pillow

Image processing enhances images or extracts useful information from the image. In this module, we will learn the basics of image processing with Python libraries OpenCV and Pillow.

Machine Learning Image Classification

In this module, you will Learn About the different Machine learning classification Methods commonly used for Computer vision, including k nearest neighbours, Logistic regression, SoftMax Regression and Support Vector Machines. Finally, you will learn about Image features.

Neural Networks and Deep Learning for Image Classification

In this module, you will learn about Neural Networks, fully connected Neural Networks, and Convolutional Neural Network (CNN). You will learn about different components such as Layers and different types of activation functions such as ReLU. You also get to know the different CNN Architecture such as ResNet and LenNet.

Object Detection

In this module, you will learn about object detection with different methods. The first approach is using the Haar Cascade classifier, the second one is to use R-CNN and MobileNet.

Project Case: Not Quite a Self-Driving Car - Traffic Sign Classification

In the final week of this course, you will build a computer vision app that you will deploy on the cloud through Code Engine. For the project, you will create a custom classifier, train it and test it on your own images.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Emphasizes practical applications, increasing relevance for those seeking to use Computer Vision in their work

Teaches essential image processing techniques using popular libraries, providing a strong foundation for further exploration

Covers a comprehensive range of topics, from fundamental concepts to advanced techniques like object detection

Instructors are experienced professionals in the field, adding credibility to the course content

Offers practical hands-on experience through labs and exercises, reinforcing learning and enhancing skill development

Requires some prior knowledge of Python and high school math, which may limit accessibility for complete beginners

Reviews summary

Building computer vision and image processing applications

learners say this course provides a diverse introduction to the principles and practices of computer vision and image processing. Students will learn about convolutional neural networks, Tensorflow, and how to apply computer vision for tasks such as image classification and object detection. Although students encounter some difficulties, most agree the course has valuable lessons for beginners and those looking to build practical skills.

The course incorporates hands-on projects that allow learners to apply concepts and build practical skills. These assignments encourage students to explore different aspects of computer vision and refine their understanding.

"The course content was good, labs were buggy and frustrating"

"This course contains a lot of information, and need time to process the information and practice on writing python codes. Overall is an excellent course."

"The course was very innovative and was awesome"

The course is well-organized and structured, making it easy for students to follow and navigate. The content is presented in a logical and coherent manner, allowing learners to build upon their knowledge gradually.

"Really structured and engaging."

"The course is very interesting, they talk in detail about how convolution helps find features in the pictures"

"This course is a perfect starter guide for those interested in Computer Vision"

Some students report encountering outdated materials and software during the course. This can be frustrating and阻碍s the learning process.

"The course is super and very understandable and summarized to the essentials. But the compulsion to use the IBM services I find not good. Nothing works"

"The final practical was difficult to navigate as Watson threw up errors."

"the Cognitive Class site is quite unstable and it makes this course a very frustrating one"

Students report a lack of support from instructors and the course team. This can be discouraging and make it difficult to resolve technical issues or receive feedback.

"I set up a 1 star because, in my opinion, it is the worst course that I ever attended"

"None of the labs worked as the course author/instructor claimed it works."

"I am very dissapointed with the course."

Many learners experience technical issues throughout the course, particularly with IBM Cloud and CV Studio. These issues can be disruptive and impact the learning experience.

"There are a few issues with the labs. Please review them."

"The tool we are required to use for the final project has been broken for months."

"Computer vision material is very weak."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Computer Vision and Image Processing with these activities:

Review Python Basics

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Refreshes and reinforces core python knowledge, setting a strong foundation for the course

Browse courses on Python

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Review Python syntax and data types
Practice basic Python operations, such as loops and conditionals

Read Computer Vision: A Modern Approach

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Provides a comprehensive overview of computer vision concepts and techniques, deepening understanding

View Probability and Statistics for Computer Science on Amazon

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Read chapters relevant to the course material
Summarize key concepts and techniques

Discussion on Image Classification Techniques

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Facilitates knowledge sharing and peer learning on different image classification techniques

Browse courses on Image Classification

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Participate in discussion forums to share insights and ask questions
Present a short summary on a specific image classification technique

Four other activities

Expand to see all activities and additional details

Show all seven activities

Explore OpenCV Tutorial

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Provides practical hands-on experience with OpenCV, enhancing understanding of image processing techniques

Browse courses on OpenCV

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Follow OpenCV tutorials to learn basic image operations
Practice image processing tasks using OpenCV

Build a Simple Image Filter

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Reinforces image processing concepts and allows students to apply knowledge in a practical way

Browse courses on Image Processing

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Design and implement a simple image filter using OpenCV
Test and evaluate the filter on different images

Attend Computer Vision Hackathon

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Provides an immersive experience for students to apply their skills and collaborate with others in a competitive setting

Browse courses on Computer Vision

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Form a team and develop a computer vision project
Present the project and receive feedback from experts

Contribute to Open Source Computer Vision Projects

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Encourages collaboration and practical implementation, enhancing understanding of real-world applications

Browse courses on Open Source

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Find open source projects in computer vision
Identify areas for contribution, such as bug fixes or feature enhancements

Career center

Learners who complete Introduction to Computer Vision and Image Processing will develop knowledge and skills that may be useful to these careers:

Researcher

Researchers contribute to the advancement of computer science and technology. In this course, you will learn how to use computer vision to conduct cutting-edge research. These skills are essential for Researchers, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Researcher

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. In this course, you will learn how to use computer vision to train and deploy machine learning models. These skills are essential for Machine Learning Engineers, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Machine Learning Engineer

Computer Vision Engineer

Computer Vision Engineers design and build systems to process and analyze images and videos. In this course, you will learn the fundamentals of computer vision, including image processing, feature extraction, and object recognition. You will also gain experience using popular computer vision libraries such as OpenCV and Pillow. These skills are essential for Computer Vision Engineers, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Computer Vision Engineer

Analyst

Analysts collect and analyze data to make informed decisions. In this course, you will learn how to use computer vision to collect and analyze data. These skills are becoming increasingly important for Analysts, as more and more data is being generated in visual form. By taking this course, you can gain the skills you need to become a successful Analyst in the computer vision field.

See salaries and explore the career path for Analyst

Robotics Engineer

Robotics Engineers design and build robots. In this course, you will learn how to use computer vision to control robots. These skills are essential for Robotics Engineers, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Robotics Engineer

Data Scientist

Data Scientists use data to solve business problems and make informed decisions. In this course, you will learn how to use computer vision to extract insights from images and videos. This skill is becoming increasingly important for Data Scientists, as more and more organizations adopt computer vision technology. By taking this course, you can gain the skills you need to become a successful Data Scientist in the computer vision field.

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Software Engineer

Software Engineers design and build software applications. In this course, you will learn how to use computer vision to develop software applications. These skills are essential for Software Engineers, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Software Engineer

UI/UX Designer

UI/UX Designers design and build user interfaces. In this course, you will learn how to use computer vision to improve the user experience of software applications. These skills are becoming increasingly important for UI/UX Designers, as more and more applications adopt computer vision technology. By taking this course, you can gain the skills you need to become a successful UI/UX Designer in the computer vision field.

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Product Manager

Product Managers manage the development and launch of new products. In this course, you will learn how to use computer vision to develop new products and features. These skills are becoming increasingly important for Product Managers, as more and more products adopt computer vision technology. By taking this course, you can gain the skills you need to become a successful Product Manager in the computer vision field.

See salaries and explore the career path for Product Manager

Professor

Professors teach and conduct research at universities and colleges. In this course, you will learn how to use computer vision to teach and conduct research. These skills are essential for Professors, and this course will help you build a strong foundation for a successful career in this field.

See salaries and explore the career path for Professor

Consultant

Consultants advise businesses on how to improve their operations. In this course, you will learn how to use computer vision to improve business operations. These skills are becoming increasingly important for Consultants, as more and more businesses adopt computer vision technology. By taking this course, you can gain the skills you need to become a successful Consultant in the computer vision field.

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Entrepreneur

Entrepreneurs start and run their own businesses. In this course, you will learn how to use computer vision to develop and launch new businesses. These skills are essential for Entrepreneurs, and this course will help you build a strong foundation for a successful career in this field.

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Lawyer

Lawyers represent clients in legal matters. In this course, you will learn how to use computer vision to assist in legal matters. These skills are becoming increasingly important for Lawyers, as more and more visual evidence is being used in court cases. By taking this course, you can gain the skills you need to become a successful Lawyer in the computer vision field.

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Journalist

Journalists gather and report news and information. In this course, you will learn how to use computer vision to gather and report news and information. These skills are becoming increasingly important for Journalists, as more and more news and information is being delivered in visual form. By taking this course, you can gain the skills you need to become a successful Journalist in the computer vision field.

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Doctor

Doctors diagnose and treat diseases and injuries. In this course, you will learn how to use computer vision to diagnose and treat diseases and injuries. These skills are becoming increasingly important for Doctors, as more and more medical imaging data is being generated. By taking this course, you can gain the skills you need to become a successful Doctor in the computer vision field.

See salaries and explore the career path for Doctor