ISTQB® CT Testing with Gen AI
Software Testing
Course Overview
Rapidly expanding AI tools confuse testers rather than empower them. You’ll learn tool-agnostic frameworks, prompting standards, and decision guides to choose and use AI effectively. This helps you simplify workflows, enhance productivity, and ensure your team gets value from GenAI without chaos.
Why Choose the ISTQB® CT Testing with Gen AI
· A Complete Foundation for GenAl in Testing
o Get a clear understanding of GenAl fundamentals, LLM behavior, capabilities, and limitations - tailored for software testing and QA workflows.
· Hands-On Prompt Engineering for Testing
o Learn practical prompt-engineering patterns designed specifically for test design, automation, analysis, reporting, and continuous improvement.
· Risk-Aware Al Adoption
o Build the skills to identify and mitigate hallucinations, reasoning errors, bias, data-privacy issues, security risks, and environmental impacts.
· Practical, Real Testing Applications
o Explore real test-process use cases, LLM- powered tools, architectural approaches, and integration pathways for testing organizations.
· Career & Organizational Impact
o Professionals gain stronger test design skills, faster analysis, improved coverage, and the ability to contribute to GenAl strategy and adoption roadmaps.
Duration: 2 days / 16 hours
Delivery Method: Classroom-based, Virtual Instructor-Led Training
COURSE HIGHLIGHTS
What You’ll Get with the CT Testing with Gen AI Program
Accelerate your testing career with a globally recognized qualification that equips you to work confidently with GenAI-driven testing workflows. What you’ll gain:
· GenAl Output Evaluation
o Adopt a structured approach to assess GenAl results using accuracy checks, traceability validation, hallucination control, bias detection, and risk-driven refinement.
· Community Support Access
o Join a dedicated peer and trainer group for post-training discussions, knowledge sharing, networking, and continued expert guidance.
· Interactive Live Sessions
o Three days of instructor-led learning with practical exercises and guided activities designed for immediate real-world application.
· Post-Training Learning Resources
o Well-structured materials, ready-to-use templates, and reference content accessible for 30 days after the program ends.
· Certification Preparation Support
o Practice assessments, mock exams, and personalized feedback to strengthen readiness and performance before the final exam.
This certification ensures you understand how to build safe, scalable, and measurable GenAl-enabled testing ecosystems.
PRE REQUISITES
Who Should Enroll for the CT Testing with Gen AI Program
· Testing & QA Professionals
o Testers, test analysts, automation engineers, test managers, UAT testers, and software developers.
· Anyone Needing a Practical Understanding of GenAI in Testing
o Ideal for professionals who must evaluate, adopt, or manage GenAI-enabled testing processes.
· Technology & Delivery Leaders
Project managers, quality managers, software development managers, business analysts, IT directors
Course Outline
DAY 1: GenAI Essentials & Prompt Engineering Basics
· Introduction to Generative AI for Software Testing
o GenAI foundations and key capabilities.
o Understanding LLM behavior, limitations, and practical relevance to testing.
o Core principles for using GenAI responsibly across QA processes.
· Prompt Engineering for Effective Software Testing
o Learn how to design, refine, and control prompts for test creation, requirement analysis, defect investigation, and reporting.
o Use structured prompting, chaining, context control, and guided techniques to generate high-quality test outputs.
o Understand prompt structures, system vs user prompts, and how they influence LLM behavior.
DAY 2: Advanced Prompting, Risk Management & AI Integration
· Prompt Engineering for Effective Software Testing
o How to choose the right prompting techniques for different testing tasks.
o Understand how to assess model output quality and improve reliability through systematic refinement.
o Learn evaluation methods, metrics, and AI-result validation.
· Managing the Risks of Using GenAI in Testing
o Identify common failure patterns and establish mitigation strategies.
o Understand secure usage practices, protected data handling, and organizational guardrails.
o Learn sustainability considerations when using GenAI at scale.
o Explore compliance expectations, AI guidelines, and testing-specific frameworks.
· LLM-Powered Solutions for Software Testing
o Architectural approaches for LLM-augmented testing solutions.
o Retrieval-Augmented Generation (RAG), agents, and LLM-powered components.
o How to fine-tune models and apply LLMOps practices.
o Deployment pathways for adopting GenAI inside test organizations.
· Roadmap for GenAI Adoption in Test Teams
o Steps to define a GenAI adoption plan for QA organizations.
o Change-management practices for integrating GenAI responsibly.
o How testers can contribute to an organization’s AI strategy and readiness.
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