Sunday, June 8, 2025 - 8:30am to Monday, June 9, 2025 - 5:00pm

AI for Testers

Artificial Intelligence (AI) has taken the world by storm, increasing the productivity of workers in a wide range of industries, especially software. But, it’s also understandably led to uncertainty and fear about the personal and implications for disciplines such as software testing.

If you’re interested in cutting through the hype and understanding how AI affects the testing profession, then this course is for you. In this hands-on class, you will learn how to apply AI to the testing process. A variety of techniques and tools will be introduced to help testers as they plan, execute, automate, and report software testing activities.

Key takeaways from this class include:

  • Understand how to leverage AI to support test planning and management
  • Learn how to use AI capabilities to analyze requirements, identify risks, and create test requirements
  • Understand how AI can support an effective exploratory testing process
  • Learning how to leverage AI to create and improve automated tests
  • Understand how AI can support test data management
  • Take home information on how AI assists test results analysis and reporting

Who Should Attend
This course is ideal for those who wish to use AI to increase the productivity of their current software testing activities. This includes those in hands-on testing roles and test managers. A basic understanding of artificial intelligence including a high-level knowledge of machine learning and generative AI is necessary. If you're new to AI, consider taking our Fundamentals of AI—ICAgile Certification (ICP-FAI) first.

Laptop and RDP Required
This class involves hands-on activities using sample software to better facilitate learning. Each student should bring a laptop with a remote desktop protocol (RDP) client pre-installed. Connection specifics and credentials will be supplied during class. Please work with your IT Admin before class to verify that your RDP client can be used to access a virtual machine running in the Amazon Web Services (AWS) environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.

Course Outline

Introduction to AI-Assisted Testing
What is AI-assisted testing?
Benefits of using AI in software testing (e.g., increased efficiency, improved test coverage, reduced costs)
Ethical considerations and challenges
Prompt engineering for testers
Case Study: Introduction to application to test

AI-Assisted Test Planning
Risk-based test planning
AI tools to support the test planning process
Using AI to analyze requirements
Performing risk analysis with AI
Using AI to generate tests
Leveraging AI-enabled commercial tools
Case Study: Test planning with generative AI

AI for Test Data Management
Introduction to Test Data Management
Using AI for Test Data Generation
Creating synthetic test data
Data masking and anonymization
Improving test data quality
Transforming test data sets
Using LLM APIs to automate prompting
Case Study: Improve existing test data sets

Exploratory Testing Using AI
Types of exploratory testing
Using AI to create good test charters
Using AI to perform charter-based exploratory testing
Using AI during ‘freestyle’ exploratory testing
Documenting exploratory testing results
Analyzing testing results using AI
Case Study: Perform AI-assisted exploratory testing

AI-Assisted Test Automation
AI-assisted automated testing capabilities

  • Code completion
  • Test case generation
  • Debugging failed tests
  • Refactoring and improving test scripts
  • Transforming tests
  • Documenting tests

Tools demonstration
Using AI to assist UI testing
Case Study: Create and run AI-assisted test scripts

AI for Test Analysis and Reporting
Automated test report generation
AI-based defect management

  • Defect categorization
  • Defect prioritization
  • Defect assignment

Quality management

  • Defect prediction
  • Root cause analysis
  • Generation of metrics

Optimizing automated test suites
Case Study: Using AI to manage defects

Class Retro and Wrap-up
Aha moments and discussions
Class evaluation survey

Class Daily Schedule

Sign-In/Registration 7:30 - 8:30 a.m.
Morning Session 8:30 a.m. - 12:00 p.m.
Lunch 12:00 - 1:00 p.m.
Afternoon Session 1:00 - 5:00 p.m.
Times represent the typical daily schedule. Please confirm your schedule at registration.

Training Course Fee Includes

• Digital course materials
• Continental breakfasts and refreshment breaks
• Lunches

Jonathan Kauffman
Coveros, Inc.

Jonathan Kauffman works as an agile software development and test consultant at Coveros, a company that helps organizations develop secure software using agile methods. In this role, Jonathan has helped both government and commercial organizations develop and test high-quality applications, and he has gained his experience by working with health care, biomedical device, and research organizations. Jonathan also presents at and attends Meetups to help maintain his connection with the software testing community and to stay abreast of recent industry developments. Before joining Coveros, he earned his B.S. in computer science from Allegheny College, where he published research on techniques for optimizing regression test suites.