AI and software testing A4Q
Take AI into software testing
The term Artificial Intelligence (AI) dates back to the 1950s and refers to the objective of building and programming “intelligent” machines capable of imitating human beings. Basically, Artificial Intelligence aims to mimic human intelligence. As AI systems become more human, they become less predictable, and there are unique problems and quality characteristics, which need to be considered when testing such systems.
During this course, you first learn the key aspects of AI, including history of AI and limits related to it. Then you start focusing on testing AI systems, including different strategies and metrics for Testing AI Systems as well as the general problems that typically occur during AI testing. Finally, you look at different ways of using AI to support testing and how to apply AI to testing tasks and quality management.
Target audience for this training:
Software testers & engineers, usability designers, designers. Anyone involved or interested in understanding AI in software testing. Managers seeking to understand how AI can add value in their organization. Business Analysts working seeking to understand the value of AI to the business.
Prerequisites: There are no prerequisites for participating in the course or taking the A4Q AI and Software Testing Exam.
Exam: After the course, you can take the A4Q AI and Software Testing Foundation certification exam. The exam is organized separately.
Contents of the training
1. Key Aspects of Artificial Intelligence
1.1 What are Human Intelligence and Artificial Intelligence?
1.2 History of AI
1.3 Symbolic AI
1.4 Sub-symbolic AI
1.5 Some ML Algorithms in More Detail
1.6 Applications and Limits of AI
2. Testing Artificial Intelligence Systems
2.1 General Problems with Testing AI Systems
2.2 Machine Learning Model Training and Testing
2.3 AI Test Environments 2.4 Strategies to Test AI-based Systems
2.5 Metrics for Testing AI-based Systems
3. Using AI to Support Testing
3.1 AI in Testing
3.2 Applying AI to Testing Tasks and Quality Management
3.3 AI in Component Level Test Automation
3.4 AI in Integration Level or System Level Test Automation
3.5 AI-based Tool Support for Testing
