ISTQB® AI Testing

Key Aspects of Artificial Intelligence

What are Human Intelligence and Artificial Intelligence?
History of AI
Symbolic AI
Sub-symbolic AI
Some ML Algorithms in More Detail
Applications and Limits of AI

Testing Artificial Intelligence Systems

General Problems with Testing AI Systems
Machine Learning Model Training
Testing AI Test Environments
Strategies to Test AI-based Systems
Metrics for Testing AI-based Systems

Common Test Types and Test Process for Mobile Applications

AI in Testing
Applying AI to Testing Tasks
Quality Management AI in Component Level Test Automation
AI in Integration Level or System Level Test Automation
AI-based Tool Support for Testing

Relevant Metrics in an AI-Based Testing Approach

Assess Tool Vendor Claims
Configuration of the Systems
Return on Investment (ROI)
Effects on Existing Processes
Sensibility of Test Cases
Test Case Explosion
Maintainability
Severity of the Defects Found

Intended Audience

Software Testers
QAs
Test Automation Engineers
Test Architects
Test Managers
Software Developers

Course Duration: 2 days

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ISTQB® AI Testing

Business Outcomes

Individuals who hold the ISTQB® Certified Tester- AI Testing certification should be able to accomplish the following business outcomes:

Understand the current state and expected trends of AI
Experience the implementation and testing of a ML model and recognize where testers can best influence its quality
Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability
Contribute to the test strategy for an AI-Based system
Design and execute test cases for AI-based systems
Recognize the special requirements for the test infrastructure to support the testing of AI-based systems
Understand how AI can be used to support software testing

About the Course

The ISTQB® AI Testing (CT-AI) certification extends understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI-based systems and using AI in testing.