What you'll learn

Understand key ISTQB CT-GenAI syllabus topics through targeted practice questions
Apply knowledge of Generative AI concepts, including LLMs and AI system behavior
Identify correct approaches to AI testing scenarios, including prompt evaluation and response validation
Recognize common exam question patterns used in ISTQB CT-GenAI certification tests
Strengthen understanding of hallucinations, bias, fairness, and ethical AI testing principles
Practice risk-based thinking for testing AI-driven applications
Improve accuracy and speed in answering certification-style questions
Assess their readiness using mock exams and chapter-based assessments
Identify knowledge gaps and improve weak areas before the actual exam
Build confidence in applying AI testing concepts under exam conditions

Course content

7 sections • 7 lectures • 33m total length

Introduction0:34
"ISTQB CT-Generative AI" Chapter Questions & Practice Exams Introduction17:24

Chapter 1 - Introduction to Generative AI for Software Testing2:01
1.1 Generative-AI-Foundations-and-Key-Concepts
1.1.1 AI Spectrum Symbolic AI, Classical Machine Learning, Deep Learning, and Ge
1.1.2 Basics of Generative AI and LLMs
1.1.3 Foundation, Instruction-Tuned and Reasoning LLMs
1.1.4 Multimodal LLMs and Vision-Language Models
1.2 Leveraging Generative AI in Software Testing Core Principles
1.2.1 Key LLM Capabilities for Test Tasks
1.2.2 AI Chatbots and LLM-Powered Testing Applications for Software

Chapter 2 - Prompt Engineering for Effective Software Testing2:16
2.1 Effective Prompt Development
2.1.1 Structure of Prompts for Generative AI in Software Testing
2.1.2 Core Prompting Techniques for Software Testing
2.1.3 System Prompt and User Prompt
2.2 Applying Prompt Engineering Techniques to Software Test Tasks
2.2.1 Test Analysis with Generative AI
2.2.2 Test Design and Test Implementation with Generative AI
2.2.3 Automated Regression Testing with Generative AI
2.2.4 Test Monitoring and Test Control with Generative AI
2.2.5 Choosing Prompting Techniques for Software Testing
2.3.1 Metrics for Evaluating the Results of Generative AI on Test tasks
2.3.2 Techniques for Evaluating and Iteratively Refining Prompts

Chapter 3 - Managing Risks of Generative AI in Software Testing4:05
3.1 Hallucinations, Reasoning Errors and Biases
3.1.1 Hallucinations, Reasoning Errors and Biases in Generative AI
3.1.2 Identify Hallucinations, Reasoning Errors and Biases in LLM Output
3.1.3 Mitigation techniques of GenAI hallucinations, reasoning errors and biases
3.1.4 Mitigation of Non-Deterministic Behavior of LLMs
3.2.1 Data Privacy and Security Risks Associated with Using Generative AI
3.2.2 Data Privacy and Vulnerabilities in Generative AI for Test processes
3.2.3 Mitigation Strategies to Protect Data Privacy and Enhance Security
3.3.1 The Impact of Using GenAI on Energy Consumption and CO₂ Emissions
3.4.1 AI Regulations, Standards and Frameworks Relevant to GenAI

Chapter 5 - Deploying and Integrating Generative AI in Test organizations3:50
5.1.1 Risks of Shadow AI
5.1.2 Key Aspects of a Generative AI Strategy in Software Testing
5.1.3 Selecting LLMs/SLMs for Software Test Tasks
5.1.4 Phases when Adopting Generative AI in Software Testing
5.2.1 Essential Skills and Knowledge for Testing with Generative AI
5.2.2 Building Generative AI Capabilities in Test Teams
5.2.3 Evolving Test Processes in AI-Enabled Test organizations

Requirements

Understanding of software testing concepts.
Interest in Generative AI, software testing, and modern AI technologies
No prior experience with Artificial Intelligence or Machine Learning is required
Interest in preparing for the ISTQB CT-GenAI certification exam
Familiarity with software applications and QC processes is beneficial

Description

This course contains the use of artificial intelligence. This course is designed for learners preparing for the ISTQB Certified Tester – Generative AI (CT-GenAI) certification exam and who want structured practice through chapter-wise questions and full mock exams. It is ideal for software testers, QC engineers, test analysts, test managers, developers, and IT professionals who aim to validate and strengthen their understanding of Generative AI testing concepts as defined in the ISTQB syllabus.

The course is specifically built for learners who want to improve exam readiness through practice-based learning rather than theory alone. Each chapter focuses on key CT-GenAI topics such as Generative AI fundamentals, Large Language Models (LLMs), prompt engineering concepts, AI test design techniques, hallucination detection, bias and fairness testing, ethical considerations, risk-based testing, and AI quality characteristics.

It is also suitable for beginners in AI testing who want a clear and structured way to prepare for certification, as well as experienced QC professionals who need focused revision and exam simulation. The practice questions are designed to reflect real ISTQB exam patterns, helping learners understand question formats, improve accuracy, and identify knowledge gaps.

By the end of this course, learners will be able to confidently approach the ISTQB CT-GenAI exam with improved conceptual clarity, stronger problem-solving skills, and practical familiarity with AI testing scenarios.

Who this course is for:

Software testers and QC engineers preparing for the ISTQB CT-GenAI certification exam
Developers and IT professionals working with or transitioning into AI-based applications
Test analysts, test managers, and QC leads who want structured exam practice and revision
Beginners in AI testing who want to understand Generative AI concepts through practice questions
Professionals looking to strengthen knowledge of LLMs, prompt testing, and AI validation techniques
Learners who prefer exam-focused preparation using chapter-wise questions and mock tests
Anyone aiming to improve confidence and accuracy for passing the ISTQB CT-GenAI certification exam

What you'll learn

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Course content

Introduction2 lectures • 18min

Chapter 1 - Introduction to Generative AI for Software Testing1 lecture • 2min

Chapter 2 - Prompt Engineering for Effective Software Testing1 lecture • 2min

Chapter 3 - Managing Risks of Generative AI in Software Testing1 lecture • 4min

Chapter 4 - LLM-Powered Test Infrastructure for Software Testing1 lecture • 3min

Chapter 5 - Deploying and Integrating Generative AI in Test organizations1 lecture • 4min

ISTQB CT-Generative AI Practice Exams0

Requirements

Description

Who this course is for: