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Full Description
This book offers a comprehensive introduction to AI and Machine Learning fundamentals, equipping software testers with the skills to effectively leverage AI-powered solutions for testing complex systems and AI applications. It also fully prepares readers for the ISTQB® Certified Tester AI Testing (CT-AI) certification exam.
Written in a practical and accessible way, this book offers a structured approach to AI testing based on the ISTQB® CT-AI syllabus. This book is filled with practical examples, detailed explanations, industry insights, a mock exam and chapter-based questions to prepare readers for passing the ISTQB® CT-AI exam to obtain certification.
The materials are designed for both university graduates and practitioners involved in testing AI-based systems or those seeking a deeper understanding of AI systems in general. It offers valuable take on into implementing AI-enabled solutions and enhancing the quality of AI-driven software, making it an indispensable resource.
Contents
Chapter 1: Introduction to AI
Chapter 2: Quality Characteristics for AI-based Systems
Chapter 3: Machine Learning Overview
Chapter 4 Machine Learning Data
Chapter 5: Machine Learning Functional Performance Metrics
Chapter 6: Machine Learning Neural Networks and Testing
Chapter 7: Testing AI-based Systems Overview
Chapter 8: Testing AI-specific Quality Characteristics
Chapter 9: Methods and Techniques
Chapter 10: Test Environments for AI-based Systems
Chapter 11: Using AI for Testing
