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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A4Q® Artificial Intelligence and Software Testing

    Business Outcomes 

    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.