Testing Generative AI Systems is a practical course designed for professionals who need to test, evaluate, and govern generative AI systems under real-world conditions.

Generative AI solutions behave differently from traditional software systems because the same input does not always produce exactly the same output. As a result, conventional deterministic testing approaches may not be sufficient on their own to assess quality, safety, and behaviour. This course helps participants understand that difference and develop testing methods suited to probabilistic, variable, and evolving AI systems.

Throughout the programme, learners work with realistic examples, structured testing frameworks, red-teaming exercises, and hands-on evaluation activities. Participants examine why generative AI systems fail, how risks such as hallucination, bias, toxicity, privacy issues, and drift emerge, and how those risks can change after deployment.

By the end of the course, participants will have a practical approach for evaluating GenAI systems throughout the product lifecycle rather than treating testing as a one-off activity.

What Participants Will Take Away

By the end of the day, participants will have developed:

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,
Clear guidance for integrating GenAI testing into product and delivery lifecycles.

We can organize this training at your preferred date and location.

Prerequisites

Participants should have:

Basic familiarity with digital products, AI, or software delivery,
Some exposure to AI-enabled features or systems as a user, builder, or stakeholder.

No previous experience in AI testing, data science, or machine learning is required.

Who Should Attend

This course is designed for:

QA Engineers and Test Leads responsible for AI-enabled systems,
Product Managers and Product Owners introducing generative AI features,
Developers and AI Practitioners building or integrating GenAI models and services,
Risk, Compliance, and Governance professionals overseeing AI usage,
UX, CX, and Innovation teams focused on trust, safety, and reliability.

What You Will Learn

By completing this course, participants will be able to:

Explain why traditional testing approaches can be insufficient for generative AI systems,
Identify major GenAI risk categories including 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 uncover hidden and adversarial failures,
Balance automation with human judgement in AI testing,
Integrate GenAI testing into continuous delivery and governance practices.

Training Outline

Module 1: Why Generative AI Breaks Traditional Testing

This module explores the fundamental differences between conventional software testing and testing generative AI systems.

Deterministic versus probabilistic behaviour
The impact of variable outputs on testing
Limitations of traditional pass/fail approaches
Uncertainty and behavioural variation in AI systems
Developing a different testing mindset for GenAI

Module 2: Understanding GenAI Risk and Behaviour

Participants examine the main risks associated with generative AI and how they may evolve over time.

Hallucination risks
Bias and fairness concerns
Toxic or inappropriate outputs
Privacy and sensitive data risks
Model and behavioural drift
How risks differ before and after deployment
The effect of user behaviour on system risk

Module 3: Designing Tests for Non-Deterministic Systems

This section focuses on building structured testing approaches for systems that may produce different outputs for the same request.

Define expected behaviour ranges instead of single fixed outcomes
Build test scenarios and test datasets
Use repeated testing
Evaluate output consistency and variability
Identify important edge cases
Define areas where human review is necessary

Module 4: Benchmarking and Evaluation Criteria

Participants learn how to assess GenAI quality using a broader set of measures than technical correctness alone.

Build suitable quality benchmarks
Define evaluation criteria
Assess accuracy, relevance, and usefulness
Measure safety and reliability
Combine human and automated evaluation
Create acceptance criteria for different use cases

Module 5: Red Teaming and Adversarial Testing

This module introduces approaches for testing how systems behave when faced with unexpected, manipulative, or hostile inputs.

Introduction to red teaming
Create adversarial prompts and scenarios
Surface hidden failure modes
Test security and safety controls
Evaluate guardrails
Feed red-team findings into risk management

Module 6: Testing in Production and Governance

The final module treats GenAI testing as a continuous activity that continues after deployment.

Connect production monitoring with testing
Evaluate live system behaviour
Monitor drift and emerging risks
Apply continuous evaluation
Feed testing results into governance and risk processes
Integrate GenAI testing into product and delivery lifecycles
Continuously strengthen trust, safety, and quality

Why Choose Us

Experience Testing Generative AI Systems in Australia through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

Delivery Method: Online Instructor-Led
Participation Model: Public / Private (In-house)
Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
Worldwide Access: Join our live virtual classrooms from Australia or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Testing Generative AI Systems through face-to-face Classroom Based training in Australia. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

Delivery Method: Classroom Based
Participation Model: Public / Private (In-house)
Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Testing Generative AI Systems in Australia as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

Delivery Method: Onsite
Participation Model: Private (In-house)
Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
Worldwide Onsite Delivery: Arrange the training in Australia or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

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0 – 50

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Testing Generative AI Systems Training in Australia

What Participants Will Take Away

Prerequisites

Who Should Attend

What You Will Learn

Training 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

Why Choose Us

Testing Generative AI Systems Training Course in Australia Schedule

Testing Generative AI Systems Training in Australia

What Participants Will Take Away

Prerequisites

Who Should Attend

What You Will Learn

Training 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

Why Choose Us

Online Instructor-Led Training

Classroom Based Training

Onsite Training

Testing Generative AI Systems Training Course in Australia Schedule