Certified Tester AI Testing (CT-AI) Exam Prep - Workshop Overview - Learn CT-AI fundamentals and exam prep

Sep 27, 2026

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Certified Tester AI Testing (CT-AI) Exam Prep is a tutor-led workshop built to bridge traditional software testing and AI testing for candidates pursuing CT-AI certification. It combines lectures, hands-on exercises, and guided discussions to strengthen understanding of AI fundamentals, quality characteristics, and responsible AI topics such as bias, ethics, and safety. The program covers machine learning concepts, dataset preparation and labeling, ML performance metrics, neural networks, and testing against challenges like concept drift and automation. Participants also explore advanced techniques including adversarial attacks, data poisoning, pairwise testing, A/B testing, and metamorphic testing, plus certification prerequisites requiring an ISTQB Foundation certificate.

LanguageEnglish

CategoryExam

FormatPDF

Pages2

Reading Time5 min

AccessFree to download

Workshop Overview

Target Audience

Learning Outcomes

Certification Prerequisites

Certified Tester AI Testing (CT-AI) Exam Prep Workshop Overview The Certified Tester AI Testing (CT-AI) Exam Prep workshop is designed to provide a comprehensive understanding of AI technology with a strong focus on CT-AI exam preparation. This workshop extends the foundational knowledge of software testing to enable the role of an AI Tester, ensuring participants are well-prepared for the CT-AI certification exam. This tutor-led workshop includes lectures, exercises, and discussions aimed at connecting the dots between traditional software testing and AI testing. Target Audience This workshop is ideal for: • Software Testers • Test Managers • AI Application Developers • Project Managers • Exam Candidates Learning Outcomes • Understand AI Fundamentals and Quality Characteristics: o Grasp the definition and effects of AI, including narrow, general, and super AI o Learn about quality characteristics such as flexibility, adaptability, autonomy, bias, ethics, safety, and standards specific to AI-based systems • Machine Learning Concepts and Data Handling: o Understand data preparation, forms of ML, ML workflow, and factors involved in algorithm selection o Learn about dataset quality issues, overfitting, underfitting, and data labelling for ML performance • ML Functional Performance and Neural Networks: o Gain knowledge on ML functional performance metrics, including the confusion matrix and benchmark suites o Learn about neural networks, coverage measures, and testing for concept drift in AI-based systems • Testing AI-Based Systems: o Understand the specification, challenges, and test levels of AI-based systems o Learn about testing for automation, bias, concept drift, and the use of test oracles and acceptance criteria • Advanced Testing Techniques and AI for Testing: o Learn about adversarial attacks, data poisoning, pairwise testing, A/B testing, and metamorphic testing o Understand the use of AI for test case generation, defect prediction, and testing user interfaces Certification Prerequisites • Participants must hold the ISTQB Foundation certificate to enrol in this workshop.

FAQs

Who is the CT-AI Exam Prep workshop designed for?

The workshop targets software testers, test managers, AI application developers, project managers, and exam candidates.

What learning outcomes does the workshop cover for CT-AI preparation?

Participants learn AI fundamentals and AI quality characteristics, machine learning and data handling, ML performance metrics and neural networks, and how to test AI-based systems across specification and test levels.

Which advanced testing methods and AI uses are included?

The workshop covers adversarial attacks, data poisoning, pairwise testing, A/B testing, and metamorphic testing, along with AI-assisted test case generation, defect prediction, and testing user interfaces.

What prerequisites are required to enrol?

Participants must hold the ISTQB Foundation certificate to enrol in the workshop.

Sep 27, 2026

Uploaded by Fans