location_city Virtual Platform schedule Sep 12th 02:00 - 03:30 PM place Online Meeting 2 people 46 Interested

With the seismic shift in industry and development of new technologies emerging, QA’s testing approaches are also changing, we must know the right strategies and algorithms to test. One of the latest technology emerging is Artificial Intelligence and Machine Learning. And its applications like Self driving cars, Virtual Assistants are everywhere. They have great impact in our life and most of our decisions, behaviour & destinations depend on them.

So in this presentation/Workshop i would like to present all the ways/strategies/ challenges faced while testing AI/ML applications. Join me in creating a Machine Learning application from scratch and then take it to testing stage, creating edge case scenarios and validations.

Time Management: To make sure that all people are upto date with with setup for hands-on, i will be sharing this document with the participants 12 days before in a temp slack channel, where they can share the progress and ask queries to resolve them quickly.
*No internet is required for participants if they follow the setup doc.

 
 

Outline/Structure of the Workshop

Presentation contains following three modules for attendee of different experience types:

Initiation with brief talk on AI/ML concepts [10 minutes]

  • Creating a Beer Wine Classifier [Total -> 30 minutes]
    • Understanding the problem, and coming out with human based solution of same [5 min]
    • Choosing the right machine learning algorithm to test [5 min]
    • Brainstorming possible test cases [5 min]
    • Creating a model [5 min]
    • Executing test case and validating with happy path [5 min]
    • Testing with edge case scenarios [5 min]

  • Image Classifier(CLI Version) [Total -> 30 minutes]
    • Understanding the problem, and coming out with human based solution of same [5 min]
    • Choosing the right tensorflow library to test [5 min]
    • Creating data sets [2 min]
    • Identifying multiple scenarios [3 min]
    • Creating a model [5 min]
    • Executing test case and validating with happy path [5 min]
    • Testing with edge case scenarios [5 min]
  • Android Real time Image Classifier [Total -> 10 minutes]
    • Exporting our model created in second activity to mobile application [5 min]
    • Validating the model with real time images by hovering camera openly at objects [5 min]
QA [10 min]
SUMMARY:
I will be initiating with theory and explain modular topics via slides in presentation attached.
And parallelly doing the workshop with attendees.

I will be sharing about the model creation steps, strategies and challenges that one may require/face while testing AI/ML apps

Learning Outcome

  • What is AI/ML
  • How technology is shifting towards AI, ML
  • Where does a QA step in
  • Writing test cases for happy paths and edgy scenarios
  • Challenges while testing AI,ML application
  • Maintaining test suite and updating with new upcoming data

Target Audience

This workshop is for audience of all levels (beginner, intermediate, Expert)

Prerequisites for Attendees

Understanding of STLC and attentiveness in Machine Learning and Artificial Intelligence.

schedule Submitted 9 months ago

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