ISTQB® Certified Tester
Testing with Generative AI
(CT-GenAI)
Duration of
Course
2 Days
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Accredited Training Provider of MSTB for
ISTQB® Certified Tester
Testing with Generative AI
(CT-GenAI)
18 - 19 May
CT-GenAI
ONLINE
Course Information
The ISTQB® Certified Tester – Testing with Generative AI (CT-GenAI) certification is a specialist-level programme designed to equip professionals with the knowledge and practical skills to test, validate, and leverage Generative AI (GenAI) systems in modern software environments.
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This course focuses on the unique challenges of testing GenAI applications, including Large Language Models (LLMs), prompt engineering, non-deterministic outputs, hallucinations, bias, and ethical risks.
Participants will learn how to design effective testing strategies, validate GenAI-driven systems, and integrate AI into the software testing lifecycle.
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In addition, the programme provides hands-on exposure to prompt engineering, AI-assisted testing, and enterprise adoption strategies, enabling organizations to move from experimental AI usage to structured, reliable, and scalable GenAI implementations.
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This course prepares participants for the ISTQB® CT-GenAI certification examination and supports career advancement in AI-driven quality engineering and digital transformation.
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The course structure and modules are aligned with practical GenAI testing applications, including prompt engineering, risk management, and enterprise integration.
Who Should Attend This Course
This course is suitable for :
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Software testers and QA professionals
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Test analysts, test automation engineers
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Software developers working with AI/GenAI systems
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User Acceptance Testers (UAT)
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Test managers and quality managers
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Project managers and product owners
Business analysts and digital transformation teams
Recommended for :
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AI practitioners and data professionals
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DevOps and platform engineers
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IT leaders and innovation teams
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Organizations adopting Generative AI solutions
Topics Coverage (2-Day Course)
Module 1 : Introduction to Generative AI for Software Testing
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Fundamentals of Generative AI and LLMs
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Applications of GenAI in software testing
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Chatbots, LLMs, and AI-powered tools
Module 2 : Prompt Engineering for Effective Testing
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Principles of prompt engineering
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Designing test scenarios using prompts
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Improving accuracy and consistency of AI outputs
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Evaluating and refining prompts
Module 3 : Managing Risks of Generative AI in Testing
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AI hallucinations and output reliability
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Bias and ethical considerations
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Data privacy and security risks
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Governance and compliance
Module 4 : LLM-Powered Test Infrastructure
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GenAI architecture and ecosystem
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Retrieval-Augmented Generation (RAG)
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AI agents and automated testing workflows
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LLMOps and model lifecycle management
Module 5 : Deploying and Integrating GenAI in Testing
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Enterprise adoption of GenAI
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Integration into testing lifecycle
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Change management and capability building
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Scaling GenAI for organizational use
By the End of This Course,
Participants Will Be Able To :
Upon successful completion, participants will be able to:
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Understand Generative AI concepts and real-world applications
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Apply prompt engineering techniques for software testing
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Design and execute test strategies for GenAI systems
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Identify and mitigate risks such as hallucinations, bias, and security issues
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Evaluate GenAI outputs for accuracy, reliability, and quality
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Build and manage GenAI-powered testing environments
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Integrate GenAI into existing QA and DevOps processes
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Support enterprise adoption of GenAI in software testing
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Enhance productivity using AI-assisted testing techniques
Course Duration
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Duration : 2 Days
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Total Contact Hours : 14 Hours
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Mode :
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Face-to-Face (F2F)
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Virtual Instructor-Led Training (VILT)
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Exam Information
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Certification Body :
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Malaysian Software Testing Board (MSTB)
(Local representative of ISTQB®)
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Exam Format :
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Multiple Choice Questions
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Duration: ~60 minutes
-
Pass Mark: ~65% (subject to ISTQB guidelines)
-
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Certification Validity : Lifetime
-
Certification Leve : Specialist / Advanced
Pre-Requisites
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Recommended : ISTQB® Certified Tester Foundation Level (CTFL)
-
Basic understanding of software testing principles
-
Familiarity with AI/GenAI concepts is beneficial but not mandatory
Additional Information
Training Approach
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Instructor-led, highly interactive sessions
-
Hands-on prompt engineering exercises
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Real-world GenAI testing use cases
-
Practical demonstrations and discussions
-
Exam-focused preparation
Delivery Options
-
Public training programmes
-
Corporate / in-house training
-
Customised GenAI workshops
Material Provided
-
Official ISTQB® CT-GenAI training materials
-
Sample exam questions
-
Course completion certificate
Why Choose This Course ?
-
Globally recognized GenAI Testing certification by ISTQB®
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High-demand skillset for AI-driven organizations
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Practical focus on real-world GenAI challenges
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Enables safe, reliable, and scalable AI adoption
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Applicable across industries: banking, telecom, healthcare, government, and tech
Course Information
The ISTQB® Certified Tester AI Testing (CT-AI) certification is an advanced-level programme designed to equip professionals with the knowledge and skills required to test Artificial Intelligence (AI) and Machine Learning (ML)-based systems effectively.
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This course provides a comprehensive understanding of AI fundamentals, machine learning concepts, and the unique challenges associated with testing AI-based systems. Participants will learn how to validate AI systems, ensure quality, address risks such as bias and non-determinism, and leverage AI to enhance software testing processes.
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CT-AI is aligned with modern digital transformation initiatives, where AI is increasingly embedded across enterprise systems, making it essential for quality engineering professionals to understand AI testing strategies.
​
This course prepares participants for the ISTQB® CT-AI certification examination and supports career advancement in AI-driven quality engineering.
Who Should Attend This Course
This course is suitable for :
• Software testers and QA professionals
• Test analysts, test engineers, and test consultants
• Data analysts and AI practitioners
• Software developers working with AI/ML systems
• Test managers and project managers
• User Acceptance Testers (UAT)
• IT and digital transformation professionals
Recommended for :
• Quality managers and software development managers
• Business analysts and operations teams
• IT directors and management consultants
• Professionals seeking exposure to AI testing and AI in testing
Topics Coverage (4-Day Course)
Chapter 1 : Introduction to Artificial Intelligence
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Fundamentals of AI and its applications
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Current trends and future outlook
Chapter 2 : Quality Characteristics for AI-Based Systems
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TAI-specific quality attributes
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Reliability, fairness, transparency
Chapter 3 : Machine Learning (ML) – Overview
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ML concepts and lifecycle
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Supervised vs unsupervised learning
Chapter 4 : ML – Data
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Data preparation and quality
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Bias, data integrity, and risks
Chapter 5 : ML Functional Performance Metrics
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Model evaluation metrics
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Accuracy, precision, recall, and beyond
Chapter 7 : Testing AI-Based Systems Overview
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AI testing lifecycle
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Test strategies for AI systems
Chapter 6 : ML – Neural Networks and Testing
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Neural networks fundamentals
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Testing challenges in deep learning systems
Chapter 8 : Testing AI-Specific Quality Characteristics
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Bias detection and mitigation
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Ethics, explainability, and transparency
Chapter 9 : Methods and Techniques for Testing AI Systems
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Test design techniques for AI
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Validation and verification approaches
Chapter 10 : Test Environments for AI Systems
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Infrastructure and tools
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Data pipelines and simulation environments
Chapter 11 : Using AI for Testing
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AI-driven test automation
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Intelligent test generation and optimization
By the End of This Course,
Participants Will Be Able To :
Upon successful completion, participants will be able to:
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Understand the current state and future trends of AI
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Explain key concepts of AI and machine learning in testing contexts
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Identify challenges in testing AI-based systems, including bias, ethics, and non-determinism
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Design and execute effective test strategies for AI systems
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Evaluate machine learning models using appropriate performance metrics
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Contribute to the development of AI testing frameworks and environments
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Recognize requirements for AI testing infrastructure
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Apply techniques to validate AI system quality and reliability
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Understand how AI can enhance software testing processes
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Support organizations in adopting AI-driven quality engineering practices
Course Duration
-
Duration : 4 Days
Total Contact Hours : 28 Hours
Mode :
• Face-to-Face (F2F)
• Virtual Instructor-Led Training (VILT)
Exam Information
-
Multiple Choice Questions
Duration: ~60 minutes
Pass Mark: ~65% (subject to ISTQB guidelines) -
Certification Validity: Lifetime
Certification Level: Advanced / Specialist
Pre-Requisites
• Must hold ISTQB® Certified Tester Foundation Level (CTFL) certification
• Basic understanding of software testing principles
• Familiarity with software development concepts is recommended
• Prior exposure to AI/ML concepts is beneficial but not mandatory
Additional Information
Certification Body
-
Malaysian Software Testing Board (MSTB)
(Local representative of ISTQB®)
Training Approach
-
Instructor-led, interactive sessions
-
Real-world AI testing use cases
-
Hands-on discussions and practical examples
-
Exam-focused preparation and guidance
Delivery Mode
-
Public training programmes
-
Corporate / in-house training
-
Customised AI testing workshops
Material Provided
-
Official ISTQB® CT-AI training materials
-
Sample exam questions
-
Course completion certificate
Why Choose This Course ?
-
Globally recognized AI Testing certification by ISTQB®
-
Critical skillset for AI, ML, and data-driven systems
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Supports career growth in AI Quality Engineering
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Industry-relevant for banking, telecom, healthcare, and tech sectors
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Future-ready capability for AI-driven digital transformation
ISTQB® Certified Tester Testing with Generative AI
(CT-GenAI)