istqb trainings
ISTQB® Certified Tester Specialist – Testing with Generative AI (CT-GenAI)
Course Description
This two-day intensive course provides the expertise and practical skills required to integrate Generative AI (GenAI) into the software testing lifecycle.
Participants will learn how to leverage Large Language Models (LLMs) to enhance testing productivity, master prompt engineering for QA tasks, and manage the unique risks associated with AI-driven testing solutions.
This course is intended for anyone looking to modernize their testing approach, including testers, test automation engineers, test managers, test architects, developers, and IT leaders ready to embrace AI-driven quality assurance.
This training is accredited and using training materials from Yes4Q Provider.
Upcoming Dates
Course Description
This two-day intensive course provides the expertise and practical skills required to integrate Generative AI (GenAI) into the software testing lifecycle.
Participants will learn how to leverage Large Language Models (LLMs) to enhance testing productivity, master prompt engineering for QA tasks, and manage the unique risks associated with AI-driven testing solutions.
This course is intended for anyone looking to modernize their testing approach, including testers, test automation engineers, test managers, test architects, developers, and IT leaders ready to embrace AI-driven quality assurance.
This training is accredited and using training materials from Yes4Q Provider.
Upcoming Dates
Course Outline
Introduction to Generative AI for Software Testing
- Fundamental concepts, capabilities, and limitations of LLMs.
- Principles for using GenAI responsibly in testing workflows.
Prompt Engineering for Effective Software Testing
- Designing and refining prompts for test analysis, design, and implementation.
- Advanced techniques: structured prompting, few-shot prompting, and chaining.
Managing Risks of Generative AI in Testing
- Identifying and mitigating hallucinations, bias, and reasoning errors.
- Addressing data privacy (PII), security, and ethical considerations.
LLM-Powered Test Infrastructure
- Understanding Retrieval-Augmented Generation (RAG) and AI agents.
- Operationalizing AI through LLMOps and fine-tuning strategies.
Deploying and Integrating GenAI in Test Organizations
- Defining a GenAI adoption plan and contributing to organizational AI strategy.
Key takeaways
- Master Prompting: Apply specialized prompt engineering patterns for test automation
and reporting. - Mitigate Risks: Build safe and reliable AI-enabled testing ecosystems by controlling for
bias and hallucinations. - Architect AI Solutions: Gain insight into modern AI test architectures, including RAG
and agentic tool-use. - Future-Proof Your Career: Stay competitive by mastering the tools and strategies
reshaping the quality assurance landscape. - Drive Strategy: Learn how to lead the transition to AI-driven testing within your team or
organization.
Topics covered
- Generative AI Foundations
- Prompt Engineering for QA
- AI Risk Management & Ethics
- RAG and AI-Powered Infrastructure
- AI Adoption & Strategy
Duration
Location
Online / Onsite
Language
Czech / English
Training material
Location
Onsite training can either take place in our premises on Mlynske Nivy 5, 821 09 Bratislava or in the premises of our client.
Price
- 899 EUR/person without VAT (Price for 5+ groups: ask for discount)
- Exam price: 160 EUR (without VAT)
Price includes
- 2 day intensive training
- Training materials
- Refreshment (depending of format)
- Certificate of attendance
- Report providing findings, strengths and weaknesses, ideas for improvement
Dates
See upcoming training dates or request a date.
Please note, the training will take place in case of min. 5 attendees.
Prerequisites:
- ISTQB® Certified Tester Foundation Level (CTFL) certificate is mandatory for the
exam. - No programming experience is required, making it suitable for both technical and non-technical roles.
Exam:
- 40 multiple-choice questions
- 60 minutes duration (75 minutes for non-native speakers)
- 65% pass mark
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