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ISTQB® Certified Tester AI Testing (CT-AI)
Certification Name / Module ISTQB® Certified Tester AI Testing (ISTQB CT-AI) / Foundation Specialist
Certification Body International Software Testing Qualifications Board / http://www.istqb.org
Exam Body Korean Software Testing Qualifications Board / http://www.kstqb.org
Languages English / Korean (available from 2022)
Target Audiences The Certified Tester AI Testing is suitable for anyone who is involved in testing as well as anyone interested in AI-based systems. This includes people performing activities such as test analysis, test consulting and software development.
Pre-requisites ISTQB Foundation (ISTQB_FL-SYL)
Syllabus & Sample Exam  
Exam Details
  • Type: 40 Multiple Choice Questions
  • 1~2 point per question
  • Duration: 60 mins / 75 mins (60 mins + extra 25% for non-native speakers)
  • Passing Criteria: 65% or more
Exam Fees
Exam Fee:
₩154,000 (Incl. VAT)
Exam Refund Rules:
Until the day before the exam: 100% refund
The day before the exam: 50% refund
The day of the exam: No refund
Student Discount:
Exam Fee: 20% off the regular examination fees
Audience: All full-time students enrolled in a college/university at the time of exam application
How to apply: Upload a copy of certificate of enrollment issued within a week on the 1:1 Bulletin Board on STEN (www.sten.or.kr)
Re-certification Not necessary
General Information
Course Overview
The testing of traditional systems is well-understood, but AI-based systems, which are becoming more prevalent and critical to our daily lives, introduce new challenges. This course will introduce the key concepts of Artificial Intelligence (AI), how we decide acceptance criteria and how we test AI-based systems. These systems have unique characteristics, which makes them special – they can be complex (e.g. deep neural nets), self-learning, based on big data, and non-deterministic, which creates many new challenges and opportunities for testing them.

The course will introduce the range of types of AI-based systems in use today and explain how machine-learning (ML) is often a key part of these systems and show how easy it is to build ML systems. We will look at how the setting of acceptance criteria needs to change for AI-based systems, why we need to consider ethics, and show how the characteristics of AI-based systems make testing more difficult than for traditional systems.

Three perspectives are used to show how quality can be achieved with these systems. First, we will consider the choices and checks that need to be made when building a machine-learning system to ensure the quality of data used for both training and prediction. Ideally, we want data that is free from bias and mis-labelling, but, most importantly, closely aligned with the problem. Next, we will consider the range of approaches suitable for the black-box testing of AI-based systems, such as back-to-back testing and A/B testing, introducing, in some detail, the metamorphic testing technique. Third, we will show how white-box testing can be applied to drive the testing and measure the test coverage of neural networks.
The need for virtual test environments will be demonstrated using the case of self-driving cars as an example.

Finally, the use of AI as the basis of tools that support testing will be considered by looking at examples of the successful application of AI to common testing problems.

The course is highly practical and includes many hands-on exercises, providing attendees with experience of building and testing several different types of machine learning systems. No programming experience is required.

ISTQB CT-AI Syllabus consists of the following eleven chapters:
Quality characteristics of AI-based systems / Machine learning (ML) / AI-based system testing / AI-specific quality characteristic testing / AI-based system testing methods and techniques / AI-based system testing environment / AI-based testing
Business Outcomes:
BO Id BO Text
AI 1 Understand the current state and expected trends of AI.
AI 2 Experience the implementation and testing of a ML model and recognize where testers can best influence its quality.
AI 3 Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability.
AI 4 Contribute to the test strategy for an AI-Based system.
AI 5 Design and execute test cases for AI-based systems.
AI 6 Recognize the special requirements for the test infrastructure to support the testing of AI-based systems.
AI 7 Understand how AI can be used to support software testing.
Exam Options:
Public Exam: 6 times per year (language: English) 
Post-training Exam: For those who attend training courses from KSTQB Accredited Training Providers (ATP)
Special Exam: Conducted by special requests
ISTQB Certified Tester AI Testing (CT-AI) Release History At the end of 2019, the Korean government announced the 'AI National Strategy' with a national vision of 'From an IT powerhouse to an AI powerhouse: AI for Everyone, AI of Everything'. Around the same time, KSTQB (Korean SW Testing Qualifications Board) attended the ISTQB General Assembly held in India and proposed to adopt the 'KSTQB & CSTQB AI Testing' syllabus, which we had produced and been carrying out with China, as the ISTQB AI Testing international syllabus.

As a starting point, a TF team representing various countries including Korea, China, India, Germany, UK, Spain, and Canada was formed to work on the ISTQB AI Testing syllabus (CT-AI). Through weekly online meetings, the current ISTQB CT-AI syllabus has been launched by combining the three different AI testing certification schemes that were in progress at the time reflecting the rapidly changing global AI trends.

In Korea, STA Consulting and KSTQB are the main pillars, and Dr. Stuart Reid (Testing Professional) who is CTO of STA Consulting, took the leading role of the syllabus TF team.
Dr. Stuart Reid is the chair of ISO working group (ISO/IEC/IEEE 29119) developing software testing standards.
Accredited Training Providers
Contacts info@kstqb.org
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