RiseUpp Logo
RiseUpp Logo
Machine Learning for Computer Vision
Educator Logo

Powered by

Provider Logo

Completion

CERTIFICATE

olive-leaves-logo

Machine Learning for Computer Vision

This course is part of MathWorks Computer Vision Engineer Professional Certificate.

Course Cost

Free course

Beginner

Skill Level

10 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Computer Vision for Engineering and Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

olive-leaves-logo

4.8

5,543 Enrolled

olive-leaves-logo

English

Powered by

Provider Logo
olive-leaves-logo

4.8

5,543 Enrolled

olive-leaves-logo

English

What you'll learn

  • Implement image classification workflows

  • Develop object detection systems

  • Create and evaluate machine learning models

  • Optimize model performance with custom training

  • Apply computer vision in practical applications

Skills you'll gain

Computer Vision
Machine Learning
Image Classification
Object Detection
MATLAB
Feature Engineering
Model Evaluation
Image Processing

This course includes:

11 Hours PreRecorded video

12 assignments

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo
Certificate
Certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

There are 4 modules in this course

This comprehensive course teaches machine learning applications in computer vision using MATLAB. Students learn to perform image classification and object detection tasks through hands-on projects. The curriculum covers data preparation, feature extraction, model training, and evaluation techniques. Practical applications include classifying street signs and detecting material defects, providing real-world experience in computer vision implementation.

Image Classification with Machine Learning

Module 1 · 3 Hours to complete

Image Classification Using Bag of Features

Module 2 · 2 Hours to complete

Evaluating Classification Models

Module 3 · 2 Hours to complete

Object Detection with Machine Learning

Module 4 · 3 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: MathWorks Computer Vision Engineer Professional Certificate

Reviews

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Machine Learning for Computer Vision

Beginner

Skill Level

10 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.