In the second course of the Computer Vision for Engineering and Science specialization, you will perform two of the most common computer vision tasks: classifying images and detecting objects. You will apply the entire machine learning workflow, from preparing your data to evaluating your results. By the end of this course, you’ll train machine learning models to classify images of street signs and detect material defects.
Machine Learning for Computer Vision
Machine Learning for Computer Vision
This course is part of multiple programs.
Instructors: Amanda Wang
5,674 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.8
(18 reviews)
Beginner level
Recommended experience
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Prepare data and create features for classifying images
Train & evaluate models to classify images using
Train & evaluate object detection machine learning models
Customize model training for different applications using cost matrices
Skills you'll gain
Details to know
Shareable certificate
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Assessments
12 assignments
Taught in English
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There are 4 modules in this course
What's included
6 videos6 readings4 assignments
What's included
2 videos2 readings3 assignments1 app item1 discussion prompt
What's included
3 videos2 readings2 assignments
What's included
4 videos4 readings3 assignments
Offered by
Recommended if you're interested in Machine Learning
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Frequently asked questions
Yes. A free license is available to learners enrolled in the course. You must have a computer capable of running MATLAB. You can view the system requirements here.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.