AI systems and quality
AI concepts, technologies, pre-trained models, standards, bias, ethics, safety, transparency and explainability.
A focused top-up to our practical AI Agent Testing and Evaluation training, based on the ISTQB Certified Tester AI Testing syllabus.
Connect practical agent evaluation skills with the wider concepts, risks and techniques covered by the CT-AI syllabus.
AI concepts, technologies, pre-trained models, standards, bias, ethics, safety, transparency and explainability.
Learning approaches, data preparation, training and test datasets, data quality, labelling, overfitting and underfitting.
Confusion matrices, functional performance metrics, benchmark suites, neural networks and model coverage concepts.
Test levels, test data, automation bias, concept drift, documentation, infrastructure and selecting an AI test approach.
Bias testing, non-determinism, test oracles, adversarial attacks, data poisoning, metamorphic, pairwise and back-to-back testing.
AI-assisted defect analysis, test generation, regression optimisation, defect prediction and user-interface testing.
Course coverage and delivery arrangements will be confirmed before enrolment. AI Testing Hub does not claim that this top-up itself awards the ISTQB or BCS certification unless explicitly confirmed in writing through an accredited arrangement.
The official entry requirement and exam route are controlled by ISTQB and BCS.
The ISTQB Foundation Level certificate must be obtained before taking the Certified Tester AI Testing exam.
Use this training to extend your practical AI testing skills across the syllabus topics and prepare for further study.
Choose an approved training provider or the official self-study and exam route described by BCS.
Tell us about your current ISTQB qualification and AI testing experience.