Exam Preparation: ISTQB CT-AI (v2.0)

About this course

This course contains the use of artificial intelligence.Welcome to the "Exam Preparation: ISTQB CT-AI" Course!This course is your complete guide to understanding and mastering the concepts required to successfully pass the ISTQB Certified Tester – AI Testing (CT-AI) exam.It has been carefully designed based on the official syllabus, covering all key topics step by step — from AI fundamentals, through machine learning concepts, to practical approaches for testing AI-based systems.Whether you're a software tester looking to expand your skills into AI, or preparing specifically for the CT-AI certification, this course will help you build both confidence and real understanding of the subject.What You’ll Learn:AI Fundamentals & ConceptsUnderstand what artificial intelligence really is and how it differs from traditional systems. Learn about narrow, general, and super AI, as well as key AI technologies and development approaches.Quality Characteristics of AI-Based SystemsExplore critical aspects such as autonomy, adaptability, bias, ethics, transparency, and safety. Learn why quality in AI systems is more complex than in conventional software.Machine Learning EssentialsGet a clear understanding of machine learning workflows, different types of ML, and how models are built and evaluated. Learn about overfitting, underfitting, and algorithm selection.Data in Machine LearningUnderstand the importance of data preparation, dataset quality, and labeling. Learn how training, validation, and test datasets impact model performance.ML Performance MetricsMaster key metrics such as the confusion matrix and evaluation techniques for classification, regression, and clustering. Learn their limitations and how to choose the right ones.Neural Networks & Testin