Course Overview
This course is designed to introduce quality assurance professionals to the exciting intersection of AI and testing. You’ll gain a clear understanding of what AI and AI-based software actually are—and how these tools can be used to enhance the efficiency and effectiveness of testing conventional software. Additionally, you’ll learn how to tackle the unique challenges that come with testing systems built using AI.
Who Should Attend
Testers and QA professionals eager to expand their skillset with emerging technologies that are reshaping the future of software testing
Project/Test managers and stakeholders looking to leverage AI to boost software quality and optimize development processes
Topics Covered
What Does AI Even Mean?
Understand what qualifies as AI or AI-based software. Explore various types of AI tools with a focus on machine learning and learn the difference between non-generative and generative AI—such as large language models like ChatGPT and Gemini.
Using AI in Testing
Discover practical ways to use AI tools throughout the testing process, including:
- AI-assisted test planning (e.g. risk analysis, document generation)
- Test case and test data generation
- AI support in coding and test script implementation
- Executing codeless test scripts via AI
- GUI testing
- Defect classification and defect management
Integrating AI into Test Automation Frameworks
Learn how to bring together the power of AI and traditional test automation. We’ll show you how to integrate AI into your existing frameworks for smarter, faster, and more flexible testing.
How to Test AI-Based Software
Delve into strategies for testing systems that include AI components:
- Key quality characteristics of AI-based software—and how to evaluate them
- Identifying risk factors specific to AI-driven applications
- The crucial role of data in AI development and testing
- Techniques and infrastructure needed to effectively test AI systems