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Rafał Podraza - Testowanie Oprogramowania

Welcome to the "Exam Preparation: ISTQB CT-GenAI" Course.

This course is your complete guide to mastering the concepts, techniques, and responsibilities required to excel in testing with Generative AI, specifically designed to help you prepare for the ISTQB Certified Tester – Foundation Level Extension: Generative AI (CT-GenAI) exam.

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Welcome to the "Exam Preparation: ISTQB CT-GenAI" Course.

This course is your complete guide to mastering the concepts, techniques, and responsibilities required to excel in testing with Generative AI, specifically designed to help you prepare for the ISTQB Certified Tester – Foundation Level Extension: Generative AI (CT-GenAI) exam.

Whether you’re an experienced tester aiming to adapt your skills to the age of AI, or a QA professional looking to gain cutting-edge knowledge of LLMs, prompt engineering, and AI-assisted testing practices, this course provides a comprehensive, syllabus-based approach that will empower you to pass the exam with confidence.

What You’ll Learn:

AI Fundamentals & SpectrumUnderstand the differences between symbolic AI, classical machine learning, deep learning, and generative AI. Learn how LLMs and SLMs work, including tokenization, embeddings, and context windows.

Core Capabilities of LLMs in TestingExplore how AI supports requirements analysis, test case creation, test data generation, defect analysis, automation, and reporting across the test lifecycle.

Prompt Engineering TechniquesMaster structured prompts, prompt chaining, few-shot prompting, and meta prompting. Learn how to refine prompts for accuracy and reliability in testing tasks.

Risks & Mitigation StrategiesIdentify and address AI challenges such as hallucinations, reasoning errors, biases, and non-deterministic behavior. Learn mitigation techniques like RAG, fine-tuning, and structured review processes.

Data Privacy & SecurityDiscover how to use GenAI responsibly, with a focus on privacy-preserving practices, data protection regulations like GDPR, and security considerations in AI-powered test tools.

Standards, Regulations & EthicsExplore relevant standards (ISO/ Understand the ethical implications of using GenAI in testing and how to apply them in practice.

Test Management in AI-Enabled OrganizationsSee how tester and test manager roles evolve in AI-powered environments. Learn about hybrid teams of human testers and AI agents, and how to build GenAI strategies in test organizations.

Practical Exam PreparationTest your knowledge with practice questions designed to simulate the real ISTQB CT-GenAI exam, ensuring you gain both confidence and exam-ready skills.

Who This Course Is For:

  • Aspiring CT-GenAI Candidates: Individuals preparing for the ISTQB CT-GenAI exam who want a structured, in-depth study path.

  • QA Professionals and Testers: Testers eager to expand their expertise into AI-powered testing and gain a competitive edge in a rapidly evolving field.

  • AI & Software Practitioners: Those who want to understand how AI impacts testing processes, risks, and quality in real-world projects.

By the end of this course, you will have a thorough understanding of both the theoretical foundations and the practical applications of Generative AI in software testing. You’ll be well-prepared not only to pass the ISTQB CT-GenAI certification exam but also to apply these insights effectively in real-world testing scenarios.

Let’s begin your journey toward becoming a Certified Tester in Generative AI.

Enroll now

What's inside

Learning objectives

  • Understand the role of generative ai and llms in software testing
  • Learn how to design effective prompts for different testing tasks
  • Explore key ai capabilities such as test case creation, defect analysis, and test data generation
  • Recognize common risks like hallucinations, reasoning errors, and biases
  • Discover strategies to improve reliability and security when using genai
  • Gain awareness of data privacy, compliance, and ethical considerations
  • See how genai changes the roles of testers and test managers
  • Get practical guidance to prepare for the istqb ct-genai certification exam

Syllabus

Introduction
About instructor
Information about Exam CT‑GenAI
Introduction to Generative AI for Software Testing
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Career center

Learners who complete Exam Preparation: ISTQB CT‑GenAI will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Exam Preparation: ISTQB CT‑GenAI.
Provides a groundbreaking analysis of the surveillance capitalism that is shaping our world. It argues that surveillance capitalism new form of capitalism that is based on the exploitation of personal data.
Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.
A definitive guide to financial risk management, this handbook provides in-depth analysis of methods for measuring and managing risk in financial institutions. It covers various types of financial risk and crucial reference for professionals and advanced students in finance.
This influential book challenges conventional notions of risk and probability by focusing on the impact of rare and unpredictable events ("black swans"). It argues that these events have a disproportionate impact on the world and that we are often ill-equipped to deal with them. It's a provocative read that encourages a different way of thinking about risk and uncertainty.
Provides a practical guide to data privacy and security for IT professionals. It covers the technical and legal aspects of data privacy, as well as best practices for implementing a data privacy program.
Classic work on the right to privacy. It provides a comprehensive overview of the history of privacy law and the challenges posed by new technologies.
Provides a foundational understanding of risk management and insurance principles, making it ideal for those new to the topic or seeking a broad overview. It covers basic concepts, traditional insurance, and introductory enterprise risk management, serving as a valuable textbook for undergraduate programs and a solid starting point for professionals.
Covers the principles and practices of software testing, including test automation. It comprehensive guide for both testers and developers who want to learn more about test automation.
Covers the principles and practices of software test automation. It comprehensive guide for both testers and developers who want to learn more about test automation.
Offers a comprehensive overview of LLMs, covering their theoretical foundations, practical applications, and future directions.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Provides a comprehensive overview of the legal and ethical issues surrounding data privacy, including the collection, use, and disclosure of personal information. It is an essential read for anyone interested in understanding the legal and ethical implications of data privacy.
Provides a comprehensive overview of software testing, including both theoretical and practical aspects. It covers a wide range of topics, from test planning and design to test execution and analysis. This book good resource for anyone who wants to learn more about software testing, regardless of their experience level.
Provides a practical guide to the role of the data protection officer (DPO). It covers the legal requirements for DPOs, as well as best practices for implementing a data protection program.
Provides a comprehensive overview of data protection law. It covers the legal frameworks for data protection in different jurisdictions, as well as the key legal concepts and principles.
Focused specifically on operational risk in the financial services industry, this book provides a detailed guide to managing this critical area. It covers frameworks, techniques, and best practices for identifying, assessing, and mitigating operational risks. It's essential for professionals working in risk management within banks and financial institutions.
Offers a practical, hands-on approach to prompt engineering specifically with ChatGPT. It's an excellent resource for high school and undergraduate students getting started, providing clear examples and exercises. It serves as a useful introductory guide and additional reading to complement foundational AI courses.
This textbook provides a comprehensive treatment of financial risk management, covering market, credit, and operational risks within financial institutions. It's widely used in undergraduate and graduate finance programs and solid resource for understanding the principles and practices of financial risk management.
Aligned with international standards like ISO 31000 and the COSO ERM Framework, this book offers a comprehensive introduction to enterprise risk management. It covers identification, analysis, and treatment of various risks, including emerging trends. It's suitable for students and risk professionals seeking a thorough grounding in ERM principles and practices.
Provides a hands-on approach to prompt engineering with a focus on using the OpenAI API. It's particularly relevant for undergraduate students, graduate students, and working professionals who want to programmatically interact with LLMs. It serves as a practical guide for implementing prompt engineering techniques in applications.
Focuses on the creative aspects of prompt engineering and generating diverse language outputs. It's a good fit for students and professionals looking to go beyond basic prompting and explore more advanced techniques for creative content generation. It adds breadth by covering applications in areas like creative writing and podcasting.
Offers a critical look at common risk management practices and argues for more quantitative approaches. It challenges conventional wisdom and provides insights into improving risk assessment and decision-making. It's valuable for both students and professionals looking to refine their risk management methodologies.
Provides real-world examples and case studies of how organizations have implemented enterprise risk management. It offers practical insights into the challenges and successes of ERM implementation, making it valuable for those involved in establishing or improving an ERM program.
Explores the art and science of prediction in various fields, from weather forecasting to finance. It examines why some predictions succeed while many fail, emphasizing the importance of probability and understanding uncertainty. It offers valuable lessons for risk managers who rely on forecasting and data analysis.
This handbook provides a comprehensive guide to the interconnected areas of governance, risk management, and compliance (GRC). It covers frameworks, best practices, and practical guidance for implementing an integrated GRC program. It's a valuable reference for professionals responsible for GRC in their organizations.
Delves into practical issues and presents case studies related to the execution of Enterprise Risk Management programs. It provides insights from senior risk management professionals and explores how organizations measure the impact of ERM. It is particularly useful for understanding real-world challenges and best practices in ERM implementation.
Provides a comprehensive overview of key concepts and techniques in financial risk management, covering market risk, credit risk, and operational risk. It offers practical insights into identifying, assessing, and mitigating these risks and valuable resource for students and professionals in finance.
Focused specifically on risk management within the context of projects, this book provides practical guidance and techniques for identifying, analyzing, and responding to project risks. It's a valuable resource for project managers and teams, often used as a reference or textbook in project management programs.
This guide aims to make prompt engineering accessible with a step-by-step approach. It is well-suited for beginners and those new to the field, including high school students and those in introductory undergraduate programs. It provides practical tips and is useful for gaining a broad understanding of how to formulate effective AI prompts.
Provides a comprehensive overview of the art of software testing. It covers a wide range of topics, from the principles of software testing to the techniques that can be used to perform it. This book good resource for anyone who wants to learn more about the foundations of software testing.
Considered a classic, this book provides a historical perspective on the development of risk management and probability. It traces the evolution of our understanding of risk from ancient times to the modern era, offering valuable context for the field today. It's an engaging read for anyone interested in the intellectual history of risk.
Takes a practical approach to software testing, focusing on the skills and techniques that are essential for effective testing. It covers a wide range of topics, from test planning and design to test execution and analysis. This book good resource for anyone who wants to improve their software testing skills.
A comprehensive guide aimed at making prompt engineering accessible to a wide audience. It covers various techniques and applications for leveraging AI language models effectively. is useful for high school students through working professionals seeking a thorough introduction and practical guidance.
Explores how organizations can integrate risk management into their strategic planning process to gain a competitive advantage. It goes beyond traditional compliance-based risk management to focus on how managing risk can create value. It's relevant for senior management and strategists.
This guide offers quick tips and tricks for prompt engineering across different generative AI models, including text and image generation models. It's a practical resource for users who want to improve their immediate results with various AI tools. It's suitable for all levels looking for actionable advice.
Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
Provides a comprehensive overview of software testing principles and practices. It covers a wide range of topics, from the principles of software testing to the techniques that can be used to perform it. This book good resource for anyone who wants to learn more about the foundations of software testing.
This comprehensive handbook includes a chapter on LLMs, providing a thorough overview of their history, evolution, and applications.
While not solely focused on prompt engineering, this book provides a strong foundation in understanding how LLMs work, which is essential for effective prompting. It's suitable for undergraduate and graduate students, offering technical insights into language understanding and generation. It serves as valuable background reading for those wanting to understand the underlying mechanisms of the models they are prompting. Expected publication in September 2024.
Explores prompt engineering within the broader context of generative AI and touches upon ethical considerations. It's relevant for all levels, providing a balanced view of the technical aspects and the societal impact of generative AI. It's useful for gaining a broader understanding and considering the responsible use of AI.
This handbook is geared towards engineers working with LLMs, covering the process from concept to production. It provides a deeper technical understanding of integrating and managing LLMs, which is relevant for prompt engineers working in a development context. It is best suited for graduate students and working professionals.
Provides a clear and concise overview of the history of privacy law and the challenges posed by new technologies. It great starting point for anyone interested in learning more about data privacy.
Provides a comprehensive overview of software quality assurance, covering the principles, techniques, and tools used to ensure software quality. It valuable resource for software engineers, quality assurance professionals, and anyone involved in software development.

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