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ISTQB® Certified Tester - Testing with Generative AI

Specialized ISTQB course focused on the practical use of generative AI in software testing, from prompt engineering to risk management to integrating GenAI into testing practice.
Level
Designed for participants with basic knowledge and experience
intermediate
Course length
2 days
Language
 eu
Course code
PU00190052
ISTQB
Category:
Do you want this tailor-made course to your company? Contact us

Courses with lecturer

Term
Language
Place
Form
?
How and where the course takes place.
Price without VAT
31. 8. - 1. 9. 2026
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU00190052-0002
Price without VAT
28 700 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU00190052-0001
Price without VAT
28 700 Kč

Course description

Generative AI is fundamentally changing the way we approach test analysis, test design, test data creation, automation, and results evaluation. In this training, you will not only gain an overview of the principles and capabilities of LLM, but also a practical understanding of how to use it meaningfully and safely in real-world testing tasks. The course also addresses risks such as hallucinations, bias, security, and data protection, and shows how to systematically and responsibly implement GenAI into a testing organization. Thanks to this, you will take away knowledge that can be used both for your own practice as a tester and for the broader development of testing processes in a team or company.

Course content

Chapter 1: Introduction to Generative AI for Software Testing
  • The tester learns basics of large language models (LLMs), including tokenization and multi-modal capabilities.
  • The tester explores applications of Generative AI (GenAI) in software testing, distinguishing AI chatbot from LLM-powered test tools, and experimenting with tokenization, context windows, and multi-modal prompts.
Chapter 2: Prompt Engineering for Effective Software Testing
  • The tester learns to craft effective, structured prompts for GenAI in software testing.
  • The tester gains hands-on experience with prompt engineering techniques for software test tasks and applies them.
Chapter 3: Managing Risks of Generative AI in Software Testing
  • The tester learns to identify and mitigate hallucinations, reasoning errors, and biases when testing with GenAI.
  • The tester learns to address data privacy and security issues of GenAI in software testing.
  • The tester learns energy consumption and environmental impact of GenAI in software testing.
  • The tester learns AI regulations, standards and best practices for ethical, transparent, and secure GenAI use in software testing.
Chapter 4: LLM-Powered Test Infrastructure for Software Testing
  • The tester explores GenAI architecture like Retrieval-Augmented Generation and GenAI agents.
  • The tester learns the process to fine-tune LLMs for software test tasks.
  • The tester learns Large Language Model Operations (LLMOps) concepts for deploying and managing LLMs in software testing.
Chapter 5: Deploying and Integrating Generative AI in Test Organizations
  • The tester learns a structured roadmap for integrating GenAI into test processes.
  • The tester learns organizational transformation for GenAI integration into test processes.

Certification

The certification exam is not part of the course. It is possible to order it.

Materials

The materials are in electronic form.

Objectives

  • Understanding the basics of generative AI, LLM and their capabilities and limitations in software testing
  • Practical experience with prompt engineering for test analysis, test design, test data and automation
  • Ability to evaluate GenAI outputs and continuously improve the prompting approach
  • Overview of the main risks of GenAI, including hallucinations, bias, data protection and security
  • Orientation on how to build an LLM-powered test infrastructure and how to implement GenAI in a testing organization

Do you want this tailor-made course for your company?

Contact us

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Do you want this tailor-made course for your company?

Contact us

News with the course

Náhledový obrázek novinky
Artificial intelligence (AI) 15. 11. 2024
The practical application of AI: HubSpot increased lead conversion rate

HubSpot is an American software development company. It has 8,000 employees and branches in several countries around the world. Processes related to lead generation and qualification were time-consuming and not always efficient, reducing sales productivity.

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DHL is one of the largest logistics companies in the world. It provides transportation and delivery of parcels in many countries. However, route planning, warehouse management and demand forecasting were difficult and often inefficient.

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Why with us