In this webinar, Jennifer Bonine will discuss the impact and scope of AI in testing. She will address some of the most burning questions out there on the subject around its impact to testers and give practical advice for when and how to add AI to your testing practices.
Come join this session, where I cover the basics of AI, existing problems with testing, discuss the key ways software testing can benefit from AI and the challenges involved in implementing AI-based solutions. Attending this session will help anyone to get started with AI-based testing.
At the turn of the 19th century, the industrial revolution replaced many manual jobs and that resulted in a better quality of life. At the same time, it also led to the loss of a large number of jobs in the short term. Since then there has been a recurrent fear that technological change will spawn mass unemployment. However, the Artificial Intelligence and Machine Learning revolution, that the world has come to terms with, will be significantly different from the Industrial Revolution.
In this session, Jennifer Bonine and Rick Faulise will explore new shifts in testing paradigms. Demonstrate an AI-first testing method that integrates with your current manual and automation testing, and understand AI that aids your app teams. Re-think where you want to spend time and money in your testing team in a challenge that plagues most companies of too much to test and too little time.
Since AI driven test generation was first introduced in 2017, much has been learned. Millions of test steps were generated and executed, finding thousands of bugs. We will dig into how the technology works, where it works and doesn’t.
Sure, machine learning is nothing new. And artificial intelligence is nothing new. However, when we are starting to leverage these not-so-new “intelligence” tools in our work as test engineers, that is quite new. This webinar gives some advice based on some research over the last 2 years of burgeoning ideas about how we are going to conduct performance testing and engineering work with AI and ML.
Here is your opportunity to ask any questions to Michael Bolton. Michael is a consulting software tester and testing teacher who helps people solve testing problems that they didn’t realize they could solve.
Machine Learning (ML) or artificial intelligence (AI) tools are the hottest topics right now in the testing industry, however, QA managers and manual testers have little to no knowledge about it. Thus, Yarin, the co-founder of TestCraft will go deeply into the details of ML functionality and explain the importance of ML & codeless Selenium – with real examples, statistics, and applications.
The value of machine learning is rooted in its ability to create models that guide future actions and to discover patterns missed by the naked eye. Machine learning methods are vastly superior in analyzing potential customer churn across data from multiple sources such as transactional, social media, and CRM sources.