$529.00 USD

ONE TIME OFFER! Add on the Mask R-CNN course to develop AI Instance Segmentation Apps. We will show you how to implement and train your own road degradation detector as well as analyze the extent of the degradation in real-time!

Get it for $69 [Normally $149

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YoloV4+PyQT Object Detection Course Bundle

You, are almost there, please fill in the relevant views and then get really excited to embark on your AI in Computer Vision Journey with YOLOv4+PyQt!

What you'll get:

  • Everything in YOLOv4 Bundle Included [$196]
  • Installing PyQT for building UI [$19]
  • PyQT Crash Course
  • Creating PyQT interfaces crash course [$57]
  • Integrating YOLOv4 with PyQT [$119]
  • Social Distancing GUI with PyQT [$69]
  • App 4 - Mask Detection PyQT GUI [$69]
  • Certificate of Completion
  • FREE Updates
  • LIFETIME ACCESS
  • For only $119 [Total Value of $529]

This is perfect for you if:

  • Have been stuck in AI and deep learning and seeing little to no change.
  • Are TIRED of wasting time on StackOverflow and with endless debugging.
  • Want a shortcut to learning AI in computer vision and become an expert AI developer.
  • Don't have a lot of time to spend days/weeks debugging your app.
  • Want a fast and easy approach to learning AI-CV and reduce your time to market.

Remember if you are not happy within 30 Days, you can get a refund! 

 

What People Are Saying:

“Great to have this course. Learnt a lot and got a basic understanding of computer vision and object detection with practical code. Thank you!”

Juan Antonio

“This was an amazing course! It's a great course to learn how YOLOv4 can be applied for COVID-19 applications. Because of this course I've been able to learn some complex subjects that have challenged me for a long time.”

Shira

“Thanks you sir for teaching in an easy an understandable way. Got me up and running YOLOv4 quicker than if I'd tried on my own!!”

Mikel

“Amazing Course! Explained the difficult concepts, very well. Also I'm so glad I found your course on YOLOv4 it saved me a lot of time. Thank you!”

Gur Raunaq