ISTQB Certified Tester – Testing with Generative AI

Name: ISTQB Certified Tester – Testing with Generative AI
Rating: 4.7 (27 reviews)

Master GenAI for QA: Prompt engineering, test automation, risk mitigation & ISTQB exam prep.

Created byArno Esterhuizen

Last updated 5/2026

English

What you'll learn

Apply GenAI safely across the testing lifecycle using ISTQB-aligned techniques and structured prompts.
Generate, evaluate, and refine AI-created testware such as acceptance criteria, test cases, and reports.
Identify and mitigate hallucinations, reasoning errors, bias, and privacy risks in GenAI test outputs.
Design AI-enabled test architectures using RAG, agents, fine-tuning, and LLMOps principles.

Course content

6 sections • 19 lectures • 2h 22m total length

Generative AI Foundations and Key Concepts6:34
Understand AI evolution from symbolic to generative; explain how LLMs function, including model types (foundation, instruction-tuned, reasoning) and multimodal capabilities.
Leveraging Generative AI in Software Testing: Core Principles7:45
Explore how GenAI supports testing tasks — test analysis, design, defect reporting, and automation — using LLM reasoning and summarization.
Demo: LLMs at Work — Generating Test Cases from a Login Story6:46
Practical walkthrough showing how a prompt generates, evaluates, and refines test cases from a sample user story using ChatGPT.
Introduction to Generative AI for Software Testing Quiz

Effective Prompt Development8:30
Learn prompt structure (role + context + task + constraints) and techniques like zero-shot, few-shot, and chain-of-thought prompting.
Demo: Prompt Chain to Perfection: Practical Prompt Engineering for Testers7:30
In this demo, we’re going to practice what we learned in the last lesson — how to design, test, and refine prompts that deliver accurate results for software testing tasks.
Applying Prompt Engineering Techniques to Software Test Tasks9:22
Apply structured prompting for requirement analysis, test design, implementation, regression, and reporting.
Demo: Prompt Chaining and Human Verification for Refining Acceptance Criteria9:02
In this demo, we’ll look at how to use prompt chaining — a step-by-step technique that lets us work with GenAI iteratively to refine our results.
Demo: Functional Test Case Generation from User Stories Using AI5:23
In this demo, we’ll use GenAI to generate functional test cases from a user story, and refine them step-by-step.
Demo: Using Few-Shot Prompting to Generate Gherkin-Style Test Cases3:26
In this demo, we’ll look at using few-shot prompting to generate Gherkin-style test cases from a new user story.
Demo: Selecting Context-Appropriate Prompting Techniques for Test Tasks5:37
In this hands-on demo, we’re going to pull everything together. You’ll learn how to choose the right prompting technique for a given software-testing task — whether it needs precision, repetition, or adaptability.
Evaluate Generative AI Results and Refine Prompts for Software Test Tasks8:20
Evaluate GenAI outputs using metrics (accuracy, coverage, relevance) and iterative refinement loops for higher quality.
From Prompt to Testware
Prompt Engineering for Effective Software Testing Quiz

Hallucinations, Reasoning Errors and Biases10:16
Identify common LLM issues (fabrication, flawed reasoning, bias) and learn to detect and mitigate them.
Data Privacy and Security Risks of Generative AI in Software Testing8:59
Understand data privacy, leakage, and confidentiality concerns when using GenAI tools in QA.
AI Regulations, Standards, and Best Practice Frameworks9:03
Explore frameworks and standards (ISO/IEC 42001, EU AI Act, NIST AI RMF) relevant to software testing.
Managing Risks of Generative AI in Software Testing Quiz

Architectural Approaches for LLM-Powered Test Infrastructure7:58
Understand architecture for AI-assisted testing: APIs, RAG, vector databases, and agent frameworks.
Fine-Tuning and LLMOps: Operationalizing Generative AI for Software Testing7:51
Learn fine-tuning concepts, data selection, and operational management (deployment, CI/CD, monitoring).
LLM-Powered Test Infrastructure for Software Testing Quiz

Roadmap for the Adoption of Generative AI in Software Testing8:06
Define a GenAI adoption roadmap, phases (pilot → scale), and risk control (shadow AI, governance, and ROI).
Manage Change when Adopting Generative AI for Software Testing7:36
Identify team roles, skills, and process evolution needed for AI-enabled QA teams.
Exam Format & Tips4:46
Design a 6-Month AI Adoption Roadmap for a QA Organization
Deploying and Integrating Generative AI in Test Organizations Quiz

Requirements

Basic understanding of software testing concepts.

Description

Generative AI is reshaping the software testing world and testers who learn how to use it effectively will gain a massive career advantage. This course gives you a complete, structured, and practical guide to applying Generative AI and Large Language Models (LLMs) across the entire testing lifecycle, fully aligned with the ISTQB® Certified Tester – Foundation Level: GenAI (CT-GenAI) syllabus.

Whether you’re a manual tester, automation engineer, SDET, QA lead, or preparing for the official ISTQB exam, this course will help you confidently integrate GenAI into real testing tasks.

You’ll learn how to design structured prompts, apply prompt engineering techniques, generate high-quality acceptance criteria and test cases, analyze screenshots with multimodal prompts, and refine AI outputs using ISTQB-aligned evaluation metrics. You’ll also explore how to identify and mitigate common AI risks like hallucinations, reasoning errors, bias, privacy concerns, and security vulnerabilities.

Beyond the fundamentals, you’ll dive into modern test-AI architectures including Retrieval-Augmented Generation (RAG), vector databases, and LLM-powered test agents, plus fine-tuning concepts and LLMOps practices for deploying GenAI at scale.

Throughout the course, you’ll complete hands-on exercises and demos, including prompt chaining, few-shot prompting, test case generation, prioritization, and building a mini RAG-based test assistant.

By the end, you’ll not only master GenAI-enabled testing but be fully prepared to sit for the ISTQB CT-GenAI certification exam with confidence.

Enroll today and become the AI-empowered tester the industry needs next.

Who this course is for:

Software Testers and QA Professionals
Test Managers and QA Leads
Aspiring ISTQB® CT-GenAI Candidates
Business Analysts, SDETs, and Automation Engineers
AI-Curious Professionals in IT

ISTQB Certified Tester – Testing with Generative AI

What you'll learn

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Course content

Introduction to Generative AI for Software Testing3 lectures • 21min

Prompt Engineering for Effective Software Testing8 lectures • 57min

Managing Risks of Generative AI in Software Testing3 lectures • 28min

LLM-Powered Test Infrastructure for Software Testing2 lectures • 16min

Deploying and Integrating Generative AI in Test Organizations3 lectures • 20min

Practice Exams0

Requirements

Description

Who this course is for: