ISTQB Certified Tester Specialist Level: Testing with Generative AI (CT-GenAI)
Learn how to use ChatGPT effectively in your day-to-day testing process – from generating scripts to diagnosing errors.
Upcoming training dates:
There are no upcoming events at this time
Course fee:
- Course duration: 2 days
- Face-to-face/online training: 1,650 PLN net
- Exam: 1,150 PLN net
- The training is delivered in Polish, using materials in English
Who is it for?
This training course is aimed at:
- Individuals holding the ISTQB® Certified Tester – Foundation Level (CTFL) certificate (a prerequisite for sitting the exam)
- Testers, test analysts, test automation engineers, test managers, UAT specialists and developers who wish to use GenAI in their testing work (or who already use it and prefer to do so in an informed manner rather than ‘by feel’)
- Quality leaders, project managers and support staff (QA/Delivery/IT) who need a basic, structured overview of the applications and risks of GenAI in testing
Training programme:
1. An introduction to GenAI in software testing
- The spectrum of AI: from rule-based approaches to GenAI
- LLM fundamentals: tokenisation, embeddings, context window, non-determinism
- Model types: foundation vs instruction-tuned vs reasoning
- Multimodality (text + image) in test tasks
2. Prompt Engineering for effective testing
- The structure of a good prompt: role, context, instruction, input data, constraints, output format
- Techniques: prompt chaining, few-shot, meta prompting
- Applications in test analysis, test design, implementation and automation (including regression testing)
- Evaluating results and iteratively improving prompts
3. Managing the risks of using GenAI in testing
- Hallucinations, reasoning errors, bias – how to recognise and mitigate them
- Data privacy and security (including common attack vectors and practical mitigations)
- The energy and environmental impact of using models
- Regulations, standards and frameworks for good practice (e.g. approach to compliance)
4. LLM-based testing infrastructure
- Architecture of LLM-powered solutions for testing
- RAG (Retrieval-Augmented Generation) in the context of corporate testing knowledge
- LLM agents in the automation of testing tasks
- Fine-tuning and the basics of LLMOps (deployment and maintenance)
5. Implementing GenAI in a test organisation
- Adoption roadmap and avoiding “Shadow AI”
- Criteria for selecting LLMs/SLMs for specific testing tasks (performance, cost, capabilities)
- Building team competence and managing change in testing processes
- Fine-tuning and the basics of LLMOps (deployment and maintenance)
You will learn:
- Understand how LLMs work (tokenisation, embeddings, context) and what this means in testing practice
- Select the right model type for the task (foundation / instruction-tuned / reasoning; including multimodal)
- Write ‘production-ready’ prompts, not just ones that ‘sound nice’
- Apply GenAI to real-world tasks: requirements analysis, test generation/prioritisation, automation support, analysis of reports and results
- Assess the quality of GenAI results using metrics (e.g. accuracy, completeness, contextual relevance) and iteratively improve the outcomes
- Identify and minimise risks: hallucinations, reasoning errors, bias, and privacy and security risks
- Understand when it is worth considering RAG, agents, fine-tuning and LLMOps in testing
- Prepare the organisation for GenAI implementation: from policies and competencies to a practical adoption plan
Along with the course, you’ll receive
Printed training materials
two months’ access to the training platform
consultations with the Coach
a second attempt at the exam free of charge*
What next?
Once you have completed the training, it is worth considering further development in the field of AI-powered testing by: