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

(10 customer reviews)




What you’ll learn

  • 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

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.

Who this course is 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

Course content

  • Project Overview & Import Libraries
  • Download and explore the dataset
  • Image Visualization
  • Data Augmentation
  • Build the Convolutional Neural Network
  • Train & Evaluate performance of the model
  • Use of trained model to detect face masks on the static images
  • Use of trained model and OpenCV to detect face masks on the video streams

10 reviews for Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Devang Jain

    The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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