ISTQB® Certified Tester
AI Testing
(CT-AI)
Duration of
Course
4 Days
Accredited Training Provider of MSTB for
ISTQB® Certified Tester
Testing AI (CT-AI)
13 - 16 April
CT-AI
ONLINE
22 - 25 June
CT-AI
ONLINE
ISTQB® Certified Tester AI Testing (CT-AI)
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.
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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
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Duration : 4 Days
Total Contact Hours : 28 Hours
Mode :
• Face-to-Face (F2F)
• Virtual Instructor-Led Training (VILT)
Exam Information
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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
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Malaysian Software Testing Board (MSTB)
(Local representative of ISTQB®)
Training Approach
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Instructor-led, interactive sessions
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Real-world AI testing use cases
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Hands-on discussions and practical examples
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Exam-focused preparation and guidance
Delivery Mode
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Public training programmes
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Corporate / in-house training
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Customised AI testing workshops
Material Provided
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Official ISTQB® CT-AI training materials
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Sample exam questions
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Course completion certificate
Why Choose This Course ?
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Globally recognized AI Testing certification by ISTQB®
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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
