The prevalence of machine learning (ML) and artificial intelligence (AI) in solving complex problems has increased, leading to a demand for testing professionals to support data science and ML teams with their data, pipelines, models, services, and AI ethics. This course focuses on the unique aspects of testing ML models compared to traditional programming. It uses Python, the most popular language for ML and AI, and starts by explaining the differences between ML and traditional programming.
Building up Quality Leaders – Study Notes
The article demonstrates a comprehensive understanding of leadership qualities and their application in a professional environment. It effectively highlights the importance of traits like servanthood, charisma, communication, coaching, decisiveness, respect, and gratitude. It also includes practical examples and the emphasis on fostering a positive work environment are particularly beneficial.
What I learnt from the course – “Setting a foundation for successful test automation”
Study notes as I learned a robust foundation for effective test automation from Test Automation University's "Setting a foundation for successful test automation" course.
Test Automation for Accessibility: Study Notes
Study noted on Test Automation University Course by Marie Drake on "Test Automation for Accessibility" by Rahul Parwal, Apoorva Ram, Pallavi Hatole, Devi Prasad
Nuget package manager: Study Notes
Study notes on nuget package manager created by Rahul Parwal. This will serve as a base base for anyone starting with C#/dotnet for Automation / Development
Scaling Tests with Docker : Study Notes
Study notes on Test Automation University Course "Scaling Tests with Docker" by Carlos Kidman. Notes are prepared by Rahul Parwal, Apoorva Ram & Himani Yadav
The Whole Team Approach to Continuous Testing: Study Notes
Study notes on Test Automation University Course "The Whole Team Approach to Continuous Testing" by Elisabeth Hocke. Notes are prepared by Rahul & Apoorva

