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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
Learning objectives
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
Frequently asked questions
How can I create an account on myQA.com?
There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.
If you have been booked onto a course by your company, you will receive a confirmation email. From this email, select "Sign into myQA" and you will be taken to the "Create account" page. Complete all of the details and select "Create account".
If you have the booking number you can also go here and select the "I have a booking number" option. Enter the booking reference and your surname. If the details match, you will be taken to the "Create account" page from where you can enter your details and confirm your account.
Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.
How do QA’s virtual classroom courses work?
Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.
We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.
How do QA’s online courses work?
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.
All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.
When will I receive my joining instructions?
Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.
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.