We may earn an affiliate commission when you visit our partners.
Aije Egwaikhide
and
Joseph Santarcangelo
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/uyfseq/introduction
Two deals to help you save
Save money when you learn. Here are two deals and offers that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until July 14
Coursera Plus Annual
Work toward what's next for your career with access to 10,000+ programs. Discover emerging skills and save.
Up to
40%
off
Get offer
Valid until August 30
Google AI App Builder
Learn how to use Gemini API and API Studio with a three-course series from Google DeepMind
Take
100%
off
Get offer
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.
Read more
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.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause 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
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Reviews summary
Intro to computer vision fundamentals
According to learners, this course provides an excellent introduction to Computer Vision and Image Processing, offering a solid foundational overview of key concepts like CNNs and object detection. Many found the hands-on labs using CV Studio particularly practical and rewarding, and the final project deploying an app was seen as a great culminating activity. However, some students noted that the stated prerequisites, especially regarding Python knowledge, might be understated, leading to difficulties for true beginners. Feedback is mixed on the included IBM tools and the Code Engine deployment, which some found tricky or glitchy. While it covers many topics, some reviewers felt certain areas lacked depth, suggesting it's a good starting point but requires further study.
Covers broad topics, not always deep.
"The course covers a lot but not deeply."
"While it covers many topics, I felt some areas lacked depth."
"I see this as a good starting point but it requires further study afterwards."
Hands-on activities are useful.
"The labs using CV Studio were very practical and helped solidify the concepts."
"The final project deploying the app was a great challenge and very rewarding."
"I loved the hands-on activities."
"The practical labs reinforced my understanding."
Solid intro to core CV/IP concepts.
"Excellent introduction."
"Solid foundational course."
"A good overview covering many aspects of computer vision."
"I gained a solid foundation from completing this course."
Tools can be tricky/glitchy for some.
"CV Studio was okay, but I ran into glitches."
"I found the Code Engine deployment part tricky."
"Troubleshooting deployment during the project was frustrating."
"The tools were sometimes buggy and not intuitive for me."
May require more Python than stated.
"Requires solid Python foundation."
"I struggled with the prerequisites... you really need to be comfortable [with Python]."
"Not for beginners. The pace was too fast, and they assumed more knowledge..."
"I wish the prerequisites were more clearly stated, I needed more Python skill than I had."
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
Show steps
Refreshes and reinforces core python knowledge, setting a strong foundation for the course
Browse courses on
Python
Show steps
-
Review Python syntax and data types
-
Practice basic Python operations, such as loops and conditionals
Read Computer Vision: A Modern Approach
Show steps
Provides a comprehensive overview of computer vision concepts and techniques, deepening understanding
View
Probability and Statistics for Computer Science
on Amazon
Show steps
-
Read chapters relevant to the course material
-
Summarize key concepts and techniques
Discussion on Image Classification Techniques
Show steps
Facilitates knowledge sharing and peer learning on different image classification techniques
Browse courses on
Image Classification
Show steps
-
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
Show steps
Provides practical hands-on experience with OpenCV, enhancing understanding of image processing techniques
Browse courses on
OpenCV
Show steps
-
Follow OpenCV tutorials to learn basic image operations
-
Practice image processing tasks using OpenCV
Build a Simple Image Filter
Show steps
Reinforces image processing concepts and allows students to apply knowledge in a practical way
Browse courses on
Image Processing
Show steps
-
Design and implement a simple image filter using OpenCV
-
Test and evaluate the filter on different images
Attend Computer Vision Hackathon
Show steps
Provides an immersive experience for students to apply their skills and collaborate with others in a competitive setting
Browse courses on
Computer Vision
Show steps
-
Form a team and develop a computer vision project
-
Present the project and receive feedback from experts
Contribute to Open Source Computer Vision Projects
Show steps
Encourages collaboration and practical implementation, enhancing understanding of real-world applications
Browse courses on
Open Source
Show steps
-
Find open source projects in computer vision
-
Identify areas for contribution, such as bug fixes or feature enhancements
Review Python Basics
Show steps
Refreshes and reinforces core python knowledge, setting a strong foundation for the course
Browse courses on
Python
Show steps
Show steps
Show steps
- Review Python syntax and data types
- Practice basic Python operations, such as loops and conditionals
Read Computer Vision: A Modern Approach
Show steps
Provides a comprehensive overview of computer vision concepts and techniques, deepening understanding
View
Probability and Statistics for Computer Science
on Amazon
Show steps
Show steps
Show steps
- Read chapters relevant to the course material
- Summarize key concepts and techniques
Discussion on Image Classification Techniques
Show steps
Facilitates knowledge sharing and peer learning on different image classification techniques
Browse courses on
Image Classification
Show steps
Show steps
Show steps
- 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
Show steps
Provides practical hands-on experience with OpenCV, enhancing understanding of image processing techniques
Browse courses on
OpenCV
Show steps
Show steps
Show steps
- Follow OpenCV tutorials to learn basic image operations
- Practice image processing tasks using OpenCV
Build a Simple Image Filter
Show steps
Reinforces image processing concepts and allows students to apply knowledge in a practical way
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Design and implement a simple image filter using OpenCV
- Test and evaluate the filter on different images
Attend Computer Vision Hackathon
Show steps
Provides an immersive experience for students to apply their skills and collaborate with others in a competitive setting
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Form a team and develop a computer vision project
- Present the project and receive feedback from experts
Contribute to Open Source Computer Vision Projects
Show steps
Encourages collaboration and practical implementation, enhancing understanding of real-world applications
Browse courses on
Open Source
Show steps
Show steps
Show steps
- 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
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.
Machine Learning Engineer
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.
Computer Vision 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.
Analyst
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.
Robotics Engineer
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.
Data Scientist
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.
Software Engineer
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.
UI/UX Designer
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.
Product Manager
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.
Professor
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.
Consultant
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.
Entrepreneur
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.
Lawyer
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.
Journalist
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.
Doctor
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.
For more career information including salaries, visit:
OpenCourser.com/course/uyfseq/introduction
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Computer Vision and Image Processing.
Provides a comprehensive overview of computer vision and image processing, covers a wide range of topics from image enhancement to object detection and recognition, includes practical exercises and examples in Python.
A practical guide to deep learning for computer vision tasks, covers topics such as convolutional neural networks, image classification, and object detection, includes code examples in Python.
Save
A comprehensive textbook that covers the fundamental algorithms and techniques used in computer vision, provides a solid theoretical foundation for understanding the field.
A gentle introduction to neural networks and deep learning, covers topics such as supervised and unsupervised learning, convolutional neural networks, and recurrent neural networks.
Save
A comprehensive textbook that provides a theoretical overview of pattern recognition and machine learning, including supervised and unsupervised learning, dimensionality reduction, and graphical models.
A classic textbook that provides a comprehensive overview of digital image processing, covers a wide range of topics from image enhancement to image segmentation, includes exercises and programming assignments.
A theoretical overview of statistical learning methods, including supervised and unsupervised learning, regression, and classification.
Save
A comprehensive textbook that provides an overview of data mining techniques, including data preprocessing, clustering, classification, and association rule mining.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/uyfseq/introduction
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Effort
6 weeks of study, 3-4 hours/week (Approximately 15 hours to complete)
Level
Introductory
Via
Coursera
Institution
IBM
Instructors
Aije Egwaikhide
Joseph Santarcangelo
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
magyar nyelv
Bahasa Indonesia
ไทย
қазақша
اُردُو,
فارسی
বাংলা
پښتو
آذربایجان دیلی
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser