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ISTQB® CT-GenAI: mastering software testing and prompt engineering with generative AI
Generative AI can support testing when its outputs remain subject to verification. Explore uses for preparing scenarios and analyses, then assess their relevance to your product. Develop a practice that connects AI assistance, test quality and tester judgement.
- Duration
- 2 days 14 hours
- Code
- ISTQBCTGENAI Code
- Certification
- Certified Tester Testing with Generative AI (CT-GenAI) Certification
Accredited training for the Certified Tester Testing with Generative AI (CT-GenAI) certification.
Presentation
Generative artificial intelligence (GenAI) is transforming software testing practices, offering unprecedented automation and efficiency opportunities while introducing complex new risks. The ISTQB Certified Tester Testing with Generative AI (CT-GenAI) certification is designed for testing professionals seeking to master these emerging technologies.
This 2-day course helps you understand how large language models (LLMs) work and develop practical prompt engineering skills to optimise test analysis, design and automation. You will also learn to identify and mitigate risks specific to generative AI, such as hallucinations, bias and security vulnerabilities.
By the end of the programme, you will be fully prepared to take the ISTQB Tester Testing with Generative AI certification exam (see the Certification tab for details). This internationally recognised credential demonstrates your technical expertise. It validates your ability to drive innovation in testing strategies while ensuring an ethical and secure approach.
Oo2 is a Platinum training centre accredited by GASQ (Global Association for Software Quality). This accreditation ensures that the ISTQB CT-GenAI training and exam meet ISTQB and GASQ quality requirements, with certification recognised in more than 130 countries.
Objectives
By the end of this ISTQB course, you will be able to:
- understand fundamental generative AI concepts (LLMs, tokenisation, multimodality) and their testing applications;
- master prompt engineering techniques to generate test cases, data and automated scripts;
- identify and mitigate LLM risks, including hallucinations, bias and privacy issues;
- explore advanced architectures such as RAG and AI-based testing agents;
- define a strategy for integrating generative AI into organisational testing processes;
- prepare for and pass the ISTQB Certified Tester Testing with Generative AI certification exam.
Program
Module 1: mastering GenAI fundamentals and prompt engineering
Understanding generative AI for software testing
- Distinguishing symbolic AI, machine learning, deep learning and GenAI.
- How LLMs work, tokenisation and context windows.
- Distinguishing foundation models, instruction-tuned models and reasoning models.
- Exploring multimodal model capabilities (text and images) for testing.
Mastering prompt engineering for testing
- Structuring effective prompts (role, context, instruction, constraints).
- Applying key techniques: Prompt Chaining, Few-Shot Prompting and Meta Prompting.
- Using GenAI for test analysis (generating acceptance criteria, identifying ambiguities).
- Generating functional test cases and synthetic test data with AI.
Module 2: deploying automation, managing risks and defining strategy
Implementing GenAI for automation and test management
- Generating and maintaining automated test scripts (keyword-driven, Gherkin).
- Analysing test reports and defects with LLMs.
- Optimising test management and monitoring with AI-assisted metrics.
Managing generative AI risks
- Identifying and mitigating hallucinations, reasoning errors and bias.
- Managing security risks (prompt injection) and data privacy (GDPR).
- Assessing models' environmental impact and energy consumption.
Exploring architectures and deploying a strategy
- Understanding RAG (Retrieval-Augmented Generation) and fine-tuning.
- Using LLM-based testing agents to automate processes.
- Defining a GenAI adoption roadmap and preventing shadow AI.
Audience
This course is designed for software testing and quality professionals, including:
- testers and test analysts seeking to integrate AI into their daily work;
- test automation engineers seeking to optimise script creation;
- test managers responsible for AI strategy and governance in testing;
- developers and business analysts involved in software quality.
Prerequisites
The following prerequisites apply:
- Certification: holding ISTQB Foundation Level certification (CTFL) (page in French) is mandatory to take the CT-GenAI exam.
- Knowledge: practical experience in software testing activities is strongly recommended.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
- Case study
Course highlights
- International certification: earn a globally recognised ISTQB credential demonstrating your expertise in the latest standards (v1.0 2025).
- Future-focused skills: master advanced prompt engineering techniques (Few-Shot, Chain-of-Thought, Meta-Prompting) to maximise LLM output quality.
- Practical approach: benefit from numerous hands-on exercises on Gherkin scenario generation, code analysis and hallucination detection.
- Security and ethics: learn to secure testing processes in line with current regulations (AI Act, GDPR) and prevent data leaks.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
ISTQB® is a registered trademark of the International Software Testing Qualifications Board
GASQ® is a registered trademark of the Global Association for Software Quality (page in French)