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Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV

A Practical Hands-on Data Science Guided Project on Covid-19 Face Mask Detection using Deep Learning & OpenCV
4.1
4.1/5
(228 reviews)
10,687 students
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7.9

Classbaze Grade®

8.2

Freshness

7.3

Popularity

7.7

Material

A Practical Hands-on Data Science Guided Project on Covid-19 Face Mask Detection using Deep Learning & OpenCV
Platform: Udemy
Video: 1h 45m
Language: English
Next start: On Demand

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Classbaze Grade®

7.9 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

8.2 / 10
This course was last updated on 11/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

7.3 / 10
We analyzed factors such as the rating (4.1/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

7.7 / 10
Video Score: 7.8 / 10
The course includes 1h 45m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 8 hours 18 minutes of 153 Deep Learning courses on Udemy.
Detail Score: 9.9 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

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About the course

Would you like to learn how to detect if someone is wearing a Face Mask or not using Artificial Intelligence that can be deployed in bus stations, airports, or other public places?

Would you like to build a Convolutional Neural Network model using Deep learning to detect Covid-19 Face Mask?

If the answer to any of the above questions is “YES”, then this course is for you.

Enroll Now in this course and learn how to detect Face Mask on the static images as well as in the video streams using Tensorflow and OpenCV.

As we know, COVID-19 has affected the whole world very badly. It has a huge impact on our everyday life, and this crisis is increasing day by day. In the near future, it seems difficult to eradicate this virus completely.
To counter this virus, Face Masks have become an integral part of our lives. These Masks are capable of stopping the spread of this deadly virus, which will help to control the spread. As we have started moving forward in this ‘new normal’ world, the necessity of the face mask has increased. So here, we are going to build a model that will be able to classify whether the person is wearing a mask or not. This model can be used in crowded areas like Malls, Bus stands, and other public places.

This is a hands-on Data Science guided project on Covid-19 Face Mask Detection using Deep Learning and Computer Vision concepts. We will build a Convolutional Neural Network classifier to classify people based on whether they are wearing masks or not and we will make use of OpenCV to detect human faces on the video streams. No unnecessary lectures. As our students like to say :
“Short, sweet, to the point course”

The same techniques can be used in :

Skin cancer detection
Normal pneumonia detection
Brain defect analysis
Retinal Image Analysis

Enroll now and You will receive a CERTIFICATE OF COMPLETION and we encourage you to add this project to your resume. At a time when the entire world is troubled by Coronavirus, this project can catapult your career to another level.

So bring your laptop and start building, training and testing the Data Science Covid 19 Convolutional Neural Network model right now.

You will learn:

•How to detect Face masks on the static images as well as in the video streams.
•Classify people who are wearing masks or not using deep learning
•Learn to Build and train a Convolutional neural network
•Make a prediction on new data using the trained CNN Model

We will be completing the following tasks:

•Task 1: Getting Introduced to Google Colab Environment & importing necessary libraries

•Task 2: Downloading the dataset directly from the Kagge to the Colab environment.

•Task :3 Data visualization (Image Visualization)

•Task 4: Data augmentation & Normalization

•Task 5: Building Convolutional neural network model

•Task 6: Compiling & Training CNN Model

•Task 7: Performance evaluation & Testing the model & saving the model for future use

•Task 8: Make use of the trained model to detect face masks on the static image uploaded from the local system

•Task 9: Make use of the trained model to detect face masks on the video streams

So, grab a coffee, turn on your laptop, click on the ENROLL NOW button, and start learning right now.

What can you learn from this course?

✓ Get Hands-On Practice to classify whether a person is wearing a Face Mask or not using Deep Learning & OpenCV
✓ Make Predictive Analysis on the static images as well as in the videos to detect face masks
✓ Learn to Build and Train Convolutional Neural Network Model
✓ Learn to Test CNN models and analyze their performances

What you need to start the course?

• Basics knowledge of Python, OpenCV and Neural Networks is recommended

Who is this course is made for?

• Anyone interested in Deep Learning
• Someone who wants to learn to build Convolutional Neural Network for Image Classification
• Someone who wants to use AI to detect face masks on the images as well as in the video streams
• Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models

Are there coupons or discounts for Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV ? What is the current price?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $59. So you save $44 if you enroll the course now.
The average price is $16.2 of 153 Deep Learning courses. So this course is 7% cheaper than the average Deep Learning course on Udemy.

Will I be refunded if I'm not satisfied with the Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV course?

YES, Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV course, but there is a $44 discount from the original price ($59). So the current price is just $14.99.

Who will teach this course? Can I trust School of Disruptive Innovation?

School of Disruptive Innovation has created 14 courses that got 1,015 reviews which are generally positive. School of Disruptive Innovation has taught 41,501 students and received a 4.1 average review out of 1,015 reviews. Depending on the information available, we think that School of Disruptive Innovation is an instructor that you can trust.
Creative Learning Solutions for the Digital Age
Welcome to the School of the Disruptive Innovation. We are here to teach you what they don’t teach you in school. We are unconventional in our ways but we promise and we over-deliver.
We have a community of over 40,000+ students and 60,000+ enrollments across 166 countries. We offer courses on Data Science (Classical machine Learning, Deep learning, BigData, Data Visualization & Analysis), Android Development, Web Development, and Graphics Design.
Every course is created and delivered by professionals in the field such as Technology related courses by software engineers and business related courses are created by business experts.

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7.9

Classbaze Grade®

8.2

Freshness

7.3

Popularity

7.7

Material

Platform: Udemy
Video: 1h 45m
Language: English
Next start: On Demand

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