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
Access provided by KL University
8,911 already enrolled
Gain insight into a topic and learn the fundamentals.
23 reviews
Beginner level
Recommended experience
1 week to complete
at 10 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
Tools you'll learn
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
12 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this course
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SV
Reviewed on Mar 25, 2025
Excellent course to learn ML fundamentals in computer vision field.
