ISTQB CT‑GenAI is the specialist certification that formalizes the methods, risks and metrics required for testing applications based on Generative AI; the course offered by Bittnet Training prepares Romanian practitioners for the exam and for the practical integration of LLMs in testing processes.
The ISTQB Certified Tester – Testing with Generative AI (CT-GenAI) certification addresses the urgent need to standardize testing practices for non-deterministic systems powered by generative models. The CT‑GenAI Syllabus defines concepts, techniques and evaluation criteria for LLM, RAG, multimodal models and autonomous agents, providing an internationally recognized framework for QA professionals.
The CT-GenAI syllabus covers: architectural fundamentals (tokenization, context windows, embeddings), prompt engineering applied to testing, quality measurements (factuality, hallucination rate, execution success rate), LLM infrastructure (RAG, LLMOps) and risk management (bias, privacy, security). The white paper provides definitions and practical examples for each domain, facilitating the transition from theoretical principles to reproducible test procedures.
The CT-GenAI exam is specialist level: 40 multiple-choice questions, duration 60 minutes (+25% extension for non-native candidates) and 65% passing threshold; the prerequisite is the ISTQB Foundation Level (CTFL) certification. These parameters are important for training planning and for the validation of competences in organizations.
· Software and UAT testers: can quickly generate and validate test cases and synthetic data, but must apply metrics to detect hallucinations.
· Test Analysts and Test Automation Engineers: will integrate prompt engineering into CI/CD pipelines and define automated acceptance criteria.
· Test Managers and Quality Managers: will develop governance policies, risk assessment and adoption roadmaps.
· Developers, Project Managers, Business Analysts, IT Directors: they will benefit from a common language for evaluating vendors, estimating costs and defining the LLM‑based architecture. These practical applications are explained in the course materials and syllabus.
For responsible adoption it is recommended:
· RAG integration to reduce hallucinations;
· defining quantifiable metrics for factuality and bias;
· including LLMOps in test pipelines;
· training teams through accredited courses.
Practical prompt engineering exercises and assessment scenarios are key components of the training.
CT‑GenAI adoption provides organizations with a methodological framework to transform Generative AI from an unknown risk to a competitive advantage. For professionals in Romania, Bittnet Training offers a localized course that combines official ISTQB theory with practical exercises and exam support: a recommended option for CT‑GenAI certification preparation. Enroll in the ISTQB Certified Tester – Testing with Generative AI (CT‑GenAI) course offered by Bittnet Training to gain the skills needed to safely and effectively implement GenAI in your testing processes.
