ISTQB® Certified Tester – Testing with Generative AI

An accredited training course that covers updated ISTQB® Certified Tester – Testing with Generative AI v1.1 syllabus.

This course prepares testers and other quality professionals to effectively apply generative AI (GenAI) and Large Language Models (LLMs) across the entire testing lifecycle — from requirements analysis and test design through automation to reporting and continuous improvement. The course builds on the foundation of ISTQB® Certified Tester Foundation Level (CTFL) and extends it with practical skills in prompt engineering, evaluating GenAI outputs, and refining prompts.

Participants will become familiar not only with the benefits but also with the risks of deploying GenAI in testing — such as hallucinations, reasoning errors, bias, data privacy and security risks, environmental impact, and regulatory requirements (e.g. the AI Act). The course further covers architectural approaches to LLM-powered solutions, fine-tuning and LLMOps, and concludes with a practical framework for adopting GenAI within a testing organization, including change management.

The course is intended for both technically oriented testers and test automation engineers, as well as managers, business analysts, and other roles who need a solid understanding of GenAI in testing without requiring deep technical expertise.

Lecturer

Course outline

1. Introduction to GenAI for Software Testing

   GenAI Foundations and Key Concepts
   Leveraging GenAI in Software Testing - Core Principles

2. Prompt Engineering for Effective Software Testing

   Effective Prompt Development
   Applying Prompt Engineering Techniques
   Evaluate GenAI Results and Refine Prompts

3. Managing Risks of GenAI in Software Testing Process

   Hallucinations, Reasoning Errors and Biases
   Data Privacy and Security Risks
   Energy Consumption and Environmental Impact of GenAI
   AI Regulations, Standards and Best Practice Frameworks

4. LLM-Powered Solutions for Software Testing

   Architectural Approaches for LLM-Powered Testing Solutions
   Fine-Tuning and LLMOps - Operationalizing GenAI

5. Deploying and Integrating GenAI in Test Organizations

   Roadmap for Adoption of GenAI
   Manage Change when Adopting GenAI

Key takeaways

• Understand the fundamental concepts, capabilities, and limitations of generative AI.
• Develop practical skills in prompting large language models for software testing.
• Gain insight into the risks and mitigations of using generative AI for software testing.
• Gain insight into the applications of generative AI solutions for software testing.
• Contribute effectively to the definition and implementation of a generative AI strategy and roadmap for software testing within an organization.

Topics covered