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 Microsoft Azure environment. If you or your Admin have questions about the specific applications involved, contact our Client Support team.
Course Duration and Schedule
Two-Day Format
8:30 AM - 4:30 PM each day with a 1-hour lunch break and morning and afternoon breaks.
Three-Day Format
11:30 AM - 5:00 PM each day with afternoon breaks.
Upcoming Training
✓ Guaranteed to Run
| Course | Certification | Date | Location | Price | Register | |
|---|---|---|---|---|---|---|
| ✓ | AI for Testers | Jun 7 - Jun 8, 2026 | AI Con USA | $1,595 | Register | |
| AI for Testers | Jul 28 - Jul 30, 2026 | Virtual Classroom | $1,495 | Register | ||
| AI for Testers | Sep 1 - Sep 3, 2026 | Virtual Classroom | $1,495 | Register | ||
| AI for Testers | Sep 20 - Sep 21, 2026 | STARWEST 2026 - Anaheim, CA | $1,595 | Register |
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
Related Courses
Agile Tester
Agile Tester course from Coveros with practical strategies for secure, agile software delivery.
AI for Leaders
Harness the power of AI to drive organizational success with practical strategy, leadership, governance, and culture.
API Testing Workshop
Learn foundational API testing, including hands-on practice, best practices, tools, and techniques.
Behavior-Driven Development
Learn how to use behavior-driven development to create shared understanding, improve collaboration, and drive quality software delivery...