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Testing Generative AI Systems
- Categories:
- Product Discovery and Design Software and DevOps
- Level:
- Intermediate
- Code:
- QATGAIS
- Exam:
- Not Applicable
Overview
This course equips professionals with the skills to test, evaluate, and govern generative AI systems in real-world conditions. Participants will learn how to move beyond traditional deterministic testing approaches and adopt new methods suited to probabilistic, evolving AI behaviour.
Using practical examples, structured testing frameworks, red-teaming exercises, and hands-on evaluation activities, learners will explore why generative AI systems fail, how risks emerge over time, and how to design testing strategies that build confidence, safety, and trust, before and after deployment.
By the end of the day, participants will have:
- A practical testing strategy for a real generative AI use case
- A repeatable framework for evaluating quality, risk, and behaviour in GenAI systems
- Hands-on experience with red teaming and non-deterministic testing techniques
- Clear guidance on how to integrate GenAI testing into product and delivery lifecycles
Prerequisites
Participants should have:
- Basic familiarity with digital products, AI, or software delivery
- Exposure to AI-enabled features or systems (as a user, builder, or stakeholder)
- No prior experience in AI testing, data science, or machine learning required
Target audience
This course is designed for:
- QA engineers and test leads responsible for AI-enabled systems
- Product managers and product owners deploying generative AI features
- Developers and AI practitioners building or integrating GenAI models
- Risk, compliance, and governance professionals overseeing AI usage
- UX, CX, and innovation teams concerned with trust, safety, and reliability
What's included
Select your preferred way to learn:
What is Virtual?
Live, instructor-led training delivered online
Interactive online sessions led by subject matter experts. Learners join live classes, take part in discussions, and complete practical exercises from any location, making it easy to fit collaborative learning into busy schedules.
If you prefer to connect to a course that is taking place in a physical classroom, you can choose our Remote Access option. .
Best for: Teams and individuals who want expert guidance, real-time collaboration, and flexible access.
What's included?
1 Day instructor led course
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
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What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
By completing this course, participants will be able to:
- Explain why traditional testing approaches fail for generative AI systems
- Identify key risk categories: hallucinations, bias, toxicity, privacy, and drift
- Design testing strategies for non-deterministic and evolving outputs
- Define meaningful benchmarks and evaluation criteria for GenAI quality
- Apply red-teaming techniques to surface hidden and adversarial failures
- Balance automation and human judgement in AI testing
- Embed GenAI testing into continuous delivery and governance practices
Course outline
- Module 1: Why Generative AI Breaks Traditional Testing
- Module 2: Understanding GenAI Risk and Behaviour
- Module 3: Designing Tests for Non-Deterministic Systems
- Module 4: Benchmarking and Evaluation Criteria
- Module 5: Red Teaming and Adversarial Testing
- Module 6: Testing in Production and Governance
Exams and assessments
There are no formal exams in this course. Participants complete guided testing exercises, group challenges, and a final hands-on GenAI evaluation activity with peer and facilitator feedback.
Hands-on learning
- Analysis of real-world generative AI failures
- Group exercises designing GenAI test strategies
- Prompt-based variability and edge-case testing
- Red-teaming and adversarial testing sessions
- Iterative refinement of evaluation criteria and benchmarks
- Group reflection on risk, confidence, and system behaviour
Good to know
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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course.
Once you have purchased the Online course and have completed your registration, you will receive the necessary details to enable you to immediately access it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.
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When will I receive my certificate?
Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.