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Updated in [August 18th, 2023]

Skills and Knowledge:
This course provides learners with the skills and knowledge necessary to understand and test AI-based systems. Learners will gain an understanding of the key concepts of Artificial Intelligence (AI), how to decide acceptance criteria, and how to test AI-based systems. They will also learn about the range of types of AI-based systems in use today, how machine-learning (ML) is often a key part of these systems, and how to set acceptance criteria for AI-based systems. Additionally, learners will gain hands-on experience in building and testing different types of machine learning systems.
Professional Growth:
This course contributes to professional growth by providing learners with an introduction to ISTQB AI Testing. It covers key concepts of Artificial Intelligence (AI), how to decide acceptance criteria, and how to test AI-based systems. It also covers the range of types of AI-based systems in use today, how machine-learning (ML) is often a key part of these systems, and how to set acceptance criteria for AI-based systems. Additionally, the course provides hands-on exercises to give learners experience in building and testing different types of machine learning systems. This knowledge and experience can be applied to a variety of professional contexts, allowing learners to develop their skills and increase their value in the workplace.
Further Education:
This course provides a comprehensive introduction to ISTQB AI Testing and is suitable for preparing further education. It covers key concepts of Artificial Intelligence (AI), how to decide acceptance criteria, and how to test AI-based systems. It also covers the range of types of AI-based systems in use today, how machine-learning (ML) is often a key part of these systems, and how to set acceptance criteria for AI-based systems. Additionally, the course provides hands-on exercises to give learners experience in building and testing different types of machine learning systems. Therefore, this course is suitable for preparing further education.

Course Syllabus

Introduction to AI

Quality Characteristics for AI-Based Systems

Machine Learning (ML) – Overview

ML – Data

ML Functional Performance Metrics

ML – Neural Networks and Testing

Testing AI-Based Systems Overview

Testing AI-Specific Quality Characteristics

Methods and Techniques for the Testing of AI-Based Systems

Test Environments for AI-Based Systems

Using AI for Testing