The following are the Business Outcomes that an Arficial Intelligence and Software Testing certification holder is expected to achieve:
Perform operations such as test analysis, design, implementation, execution, and completion for a system that includes one (or more) AI-based components.
Have the capacity to use AI to support testing operations in the organization to make the testing process easier.
In the context of the organization, contribute to the evaluation of AI-based testing methodologies and related technology.
About the Course
Artificial Intelligence and human intelligence have several parallels for one simple reason: Artificial Intelligence seeks to imitate human intelligence. Artificial Intelligence (AI) is a term that dates back to the 1950s and refers to the goal of creating and programming “intelligent” machines that can mimic human behavior.
As AI systems become more human, they become less predictable, and evaluating such systems must take into account specific problems and quality characteristics.
The first of the A4Q® AI and Software Testing Syllabus’ three main chapters covers all Key Aspects of Artificial Intelligence, including its origin, Symbolic AI (human-readable AI), and where AI’s limits can be found.
The journey continues to Testing AI Systems until everyone has mastered the AI-Language. In this section, all participants will learn various techniques and metrics for testing AI systems, as well as the general issues that arise during testing.
The A4Q® AI and Software Testing Scheme’s Syllabus concludes with Using AI to Support Testing and how to apply AI to testing tasks and QM.