ISTQB® Certified Tester – Testing with Generative AI

A hands-on training program to apply artificial intelligence to software testing, with real tools and practical use cases.

70% practical training

Possible funding

A hands-on training program to apply artificial intelligence to software testing, with real tools and practical use cases. Learn how to integrate generative AI into your software testing processes with our practical training, designed specifically for testing professionals.

Throughout this course, you will explore the fundamentals of AI applied to software testing, adopt industry best practices, and discover concrete tools to automate and optimize your testing workflows.

You will gain essential skills to craft effective prompts, leverage LLMs (Large Language Models), and manage the risks of AI-related errors. You will also learn how to use conversational AI to query models like ChatGPT more efficiently, and how to integrate these technologies into your existing toolchains.

Upcoming dates

22-23 September
13-14 October
17-18 November

Training duration

2 days (14 hours)

See the programme

Certified Training

Our training is ISTQB® certified. This means that participants holding an “ISTQB® Certified Tester Foundation Level” certificate can take the official exam and obtain an internationally recognized certificate upon completion of the training.

1800 €

2 days (14 hours)
Online training
4 to 8 participants
CPF eligible
English
French and German, see here

CUSTOMISED

2 days (14 hours)
Online training or in person
4 to 8 participants
CPF eligible
English
French and German, see here

Objectives

Master the fundamentals of generative AI
Use different prompting techniques effectively
Assess the risks of using AI to accelerate software testing
Integrating generative AI into testing processes

Requirements

The training is open to everyone with no prerequisites.
However, to take the ISTQB® Certified Tester “Testing with Generative AI” certification exam, you must already hold the ISTQB® Certified Tester Foundation Level certificate.

INTER

INTRA

INTER

INTRA

1800 €

2 days (14 hours)
Online training
4 to 8 participants
CPF eligible
English
French and German, see here

CUSTOMISED

2 days (14 hours)
Online training or in person
4 to 8 participants
CPF eligible
English
French and German, see here

Objectives

Master the fundamentals of generative AI
Use different prompting techniques effectively
Assess the risks of using AI to accelerate software testing
Integrating generative AI into testing processes

Requirements

The training is open to everyone with no prerequisites.
However, to take the ISTQB® Certified Tester “Testing with Generative AI” certification exam, you must already hold the ISTQB® Certified Tester Foundation Level certificate.

What you will learn

The training content complies with the ISTQB Certified Tester syllabus ‘Testing with Generative AI’.
Smartesting is an accredited partner of ISTQB and CFTL.

1. Introduction to GenAi for Software Testing

1.1 Foundations and key concepts of generative AI
1.2 Leveraging generative AI in software testing: general principles

2. Prompt Engineering for Effective Software Testing

2.1 Effective prompt development
2.2 Applying prompt engineering techniques to software testing tasks
2.3 Evaluating generative AI results and refining queries for software testing tasks

3. Managing Risk of GenAI in Software Testing Process

3.1 Hallucinations, reasoning errors, and biases
3.2 Data confidentiality and security risks associated with generative AI in software testing
3.3 Energy consumption and environmental impact of generative AI for software testing
3.4 Regulations, standards, and best practice frameworks for AI

4. LLM-Powered Solutions for Software Testing

4.1 Architectural approaches for LLM-based testing infrastructures
4.2 Fine-tuning and LLMOps: operationalising generative AI for software testing

5. Deploying and Integrating GenAI in Test Organizations

5.1 Roadmap for adopting generative AI in software testing
5.2 Managing change when adopting generative AI for software testing

Download detailed programme

Expected results

Understand the fundamental concepts, capabilities, and limitations of generative AI
Develop practical skills in prompting large language models for software testing
Gain insight into the risks and mitigations of using generative AI for software testing
Gain insight into the applications of generative AI solutions for software testing
Contribute effectively to the definition and implementation of a generative AI strategy and roadmap for software testing within an organization

Passing the ISTQB® certification

The ISTQB® international certification ‘Certified Tester – Testing with Generative AI’ demonstrates the acquisition of essential knowledge and skills for integrating GenAI functionalities in a responsible manner.

It also validates the ability to manage key risks: hallucinations, bias, security, confidentiality and environmental impact.

The exam, in the form of a 40-question multiple-choice test, takes place at the end of the session and lasts approximately one hour. A passing score is achieved with 26 correct answers, or 65%.

See the syllabus

Satisfied professionals

99%

Satisfaction rate*

100%

Success rate in skills assessments*

* Data updated annually - January 2025

“This training course will change your daily life! It enabled me to understand how AI works and to experiment with its use (or ‘its strengths and weaknesses’, if you prefer) in all aspects of software testing. I clicked, adjusted, analysed, refined, compared… Today, I know how to choose where and how to implement AI in my project context so that it brings the most value. Do as I did, gain expertise and move from attraction to action!”

Nicolas MANDIL
Agile Software QA & Lead QA – Freelance

“Extremely relevant training, with an excellent balance between theory and practice.
It provides a solid foundation, an excellent overview and tools to get started right away.”

Samuel-Alexandre Massot
Product Validation Manager – Kayentis

“It is, to say the least, one of the most interesting training courses I have ever attended and I highly recommend it.”

Arthur Gaudé-Pasquet
QA Tester – Onepoint

Our tutors

BRUNO LEGEARD

Bruno is a recognised expert in AI applied to software testing. At Smartesting, he is involved in developing tools that integrate AI and evaluating generative AI for testing. Highly involved in the community, he contributes to the work of the CFTL and ISTQB®, for which he co-authored the syllabus ‘Testing with Generative AI’ as technical lead.

ANNE KRAMER

Since 2006, Anne has been promoting Model-Based Testing through her work as a project manager, consultant, trainer and author. When she joined Smartesting in 2022, she turned her attention to Large Language Models and generative AI, exploring their use in software testing. Co-author of the ISTQB® syllabus ‘Testing with Generative AI’, she now shares her experience to support professionals in this evolution.

FABRICE BOUQUET

A professor of computer science at Marie and Louis Pasteur University, Fabrice is a specialist in software testing and artificial intelligence. With a PhD in computer science, he has more than 100 publications to his name and has been involved in numerous research projects and industrial collaborations. Passionate about the link between theory and practice, he shares his expertise and enthusiasm in the training courses he leads.

ABBAS AHMAD

Abbas est docteur en informatique, formateur accrédité ISTQB® et expert en tests logiciels depuis plus de six ans. Président de l’UAESTQB et PDG de Certilog FZCO, il accompagne les organisations dans la mise en œuvre de solutions de test efficaces, notamment dans l’IoT et l’IA. Contributeur à plusieurs projets européens sur la cybersécurité et le test de l’IA, il est également product owner de la certification ISTQB® “Tester avec l’IA générative”.

ETIENNE DUFOUR

With nearly 15 years of experience in software testing, Etienne supports the 350 testers at AXA France’s Test Guild with methods and tools. His current work focuses on digital accessibility and the use of generative AI to strengthen testing practices. Very involved in the community, he regularly shares his expertise at conferences such as JFTL.

Everything you need to know about training

Target audience

Teaching methods

Moyens pédagogiques

Accessibility

Quality Engineers, QA Managers
Testers, Testing Consultants
Developers, Test Automation Engineers
Product Owners, Project Managers
Business Analysts
…

Remote/face-to-face depending on the session
Needs analysis prior to training
Adjustments during training based on trainee feedback
Satisfaction survey at the end of training
Teaching resources: Practical workshops, presentation materials, use of generative AI
Teaching methods: Theoretical, active, questioning
Required equipment: A computer equipped with a camera, microphone, and speakers or headphones. Google browser.

Ateliers pratiques, support de présentation, utilisation d’IA génératives
Mise à disposition de la plateforme de pratique multi-LLM : Smartesting LLM workbench
Utilisation de LLM et d’outils IA pour la formation :
- GPT-5, GPT-5-mini, GPT-5-nano – OpenAI
- Mistral Nemo et Large, Pixtral, Codestral – Mistral
- Claude-4 en versions Opus, Sonnet et Haiku – Anthropic
- Gemini 2 Flash, Pro et Thinking – Google
- LLM workbench, Application RAG, et AI Test Runner (agent IA) – Smartesting

La formation évoluera en continu pour intégrer les avancées technologiques les plus pertinentes en conformité avec les évolutions de la certification ISTQB® “Tester avec l’IA générative”.

Ateliers pratiques, support de présentation, utilisation d’IA génératives
Mise à disposition de la plateforme de pratique multi-LLM : Smartesting LLM workbench
Utilisation de LLM et d’outils IA pour la formation :
- GPT-5, GPT-5-mini, GPT-5-nano – OpenAI
- Mistral Nemo et Large, Pixtral, Codestral – Mistral
- Claude-4 en versions Opus, Sonnet et Haiku – Anthropic
- Gemini 2 Flash, Pro et Thinking – Google
- LLM workbench, Application RAG, et AI Test Runner (agent IA) – Smartesting

A preliminary interview will be arranged to tailor the training to your disability.
Our instructors know how to adapt their teaching methods to different disabilities.
Disability contact: Maëva Legeard, 03.56.89.43.43 or maeva.legeard@smartesting.com

Target audience

Quality Engineers, QA Managers
Testers, Testing Consultants
Developers, Test Automation Engineers
Product Owners, Project Managers
Business Analysts
…

Teaching methods

Remote/face-to-face depending on the session
Needs analysis prior to training
Adjustments during training based on trainee feedback
Satisfaction survey at the end of training
Teaching resources: Practical workshops, presentation materials, use of generative AI
Teaching methods: Theoretical, active, questioning
Required equipment: A computer equipped with a camera, microphone, and speakers or headphones. Google browser.

Moyens pédagogiques

Ateliers pratiques, support de présentation, utilisation d’IA génératives
Mise à disposition de la plateforme de pratique multi-LLM : Smartesting LLM workbench
Utilisation de LLM et d’outils IA pour la formation :
- GPT-5, GPT-5-mini, GPT-5-nano – OpenAI
- Mistral Nemo et Large, Pixtral, Codestral – Mistral
- Claude-4 en versions Opus, Sonnet et Haiku – Anthropic
- Gemini 2 Flash, Pro et Thinking – Google
- LLM workbench, Application RAG, et AI Test Runner (agent IA) – Smartesting

Moyens pédagogiques

Ateliers pratiques, support de présentation, utilisation d’IA génératives
Mise à disposition de la plateforme de pratique multi-LLM : Smartesting LLM workbench
Utilisation de LLM et d’outils IA pour la formation :
- GPT-5, GPT-5-mini, GPT-5-nano – OpenAI
- Mistral Nemo et Large, Pixtral, Codestral – Mistral
- Claude-4 en versions Opus, Sonnet et Haiku – Anthropic
- Gemini 2 Flash, Pro et Thinking – Google
- LLM workbench, Application RAG, et AI Test Runner (agent IA) – Smartesting

Accessibility

A preliminary interview will be arranged to tailor the training to your disability.
Our instructors know how to adapt their teaching methods to different disabilities.
Disability contact: Maëva Legeard, 03.56.89.43.43 or maeva.legeard@smartesting.com

Our partners

Our certifications

We Answer Your Questions

What is the difference between in-house and public training?

An in-house training session is organized exclusively for employees of the same company. It is customized to your specific needs and can take place on your premises.
A public training session brings together participants from different companies. It follows a standard program and encourages knowledge-sharing with professionals from various backgrounds.

What makes us experts in AI?

At Smartesting, innovation is at the heart of everything we do. We integrate AI directly into our solutions and continuously explore new ways to transform software testing practices. This innovation is driven by a dedicated R&D team and high-level academic partnerships. This dynamic motivates us to share our expertise through practical training, based on real-world use cases and feedback from our projects.

What funding options are available for the training?

Self-financing: you pay the training cost directly.
Company funding: through your organization’s skills development plan.
Via an OPCO (Competence Operator): your company’s OPCO can cover all or part of the training costs.

What are the benefits of an ISTQB®-certified training?

The ISTQB® certification is an international benchmark in the field of software testing. It enhances your professional profile, facilitates career growth towards specialized roles, and enables you to apply recognized methods to improve the quality and efficiency of testing. It is also an excellent way to join an active professional community and progress through the different certification levels.

Our selection of generative AI

At Smartesting, innovation is at the heart of our activities. We integrate AI in a practical way into our solutions and are constantly exploring new ways to transform software testing practices. This dynamic drives us to share our experience through practical training courses based on real use cases and feedback from our projects.

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