Getting Started with AI and Testing

AI has been rapidly changing the way we approach software testing. Traditional test automation is time-consuming to create and breaks down easily in the presence of change. Thankfully, AI is helping testing teams create less procedural, more resilient tests that are able to self-heal in the presence of modern, rapidly changing, highly dynamic production systems.

This sounds great, but you may be asking yourself: How do I get started? What additional skills do I need to learn? What tools are available for me to start using, right now? Join Dionny Santiago as he breaks down different AI techniques and applies them to different testing problems.

Discover freely available tools that will help you start building stronger, more resilient AI-enabled test automation today. Want to tackle the hardest of challenges, and want to learn how to generate new test cases? We will also cover open source tools that can help you build your own neural networks for tackling tough testing problems. No prior programming or AI/ML experience needed!.

Dionny Santiago, test.ai

Dionny Santiago is an engineering leader with over 13 years of experience primarily focused on software testing and test automation. Dionny's goal is to advance the current state of the art in software testing through the application of Artificial Intelligence and Machine Learning.

Dionny holds a M.S. degree and is currently pursuing a Ph.D. in Computer Science from Florida International University (FIU). He has published and contributed to the design of test specification languages and AI-driven test generation approaches.

Dionny also enjoys attending software testing conferences to both learn and share. Dionny is a member of the IEEE Computer Society and the ACM.