You can pass the 40 questions long ISTQB Certified Tester AI Testing (CT-AI) exam with the right study approach and solving practice test questions. Get some practical study tips and explore more about AI testing.
The (CT-AI) ISTQB AI Testing certification talks about the knowledge of artificial intelligence and/or deep (machine) learning. The certification is most specifically on testing AI-based systems and using AI in testing.
Target Audience for the CT-AI Exam:
The Certified Tester AI Testing certification targets anyone involved in testing AI-based systems or AI for testing. The certification includes people in roles such as test analysts, data analysts, testers, test engineers, test consultants, test managers, software developers, and user acceptance testers. The CT-AI certification is also suitable for aspirants who want a basic knowledge of testing AI-based systems and AI for testing. This may include business analysts, operations team members, project managers, quality managers, software development managers, IT directors, and management consultants.
Are There Any Eligibility Criteria to Take the CT-AI Exam?
To earn the CT-AI certification, a candidate must hold the Certified Tester Foundation Level certificate.
What Skills Do You Earn through the CT-AI Certification Exam?
Aspirants who earn the ISTQB Certified Tester- AI Testing certification should be able to have the following business outcomes:
- They can understand the current state and expected trends of AI.
- Offer to the test strategy for an AI-Based system.
- They would learn about the implementation and testing of an ML model and recognize where testers can best change its quality.
- The CT-AI aspirant would learn about AI-based system’s challenges, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency, and explainability.
- They would Design and execute test cases for AI-based systems.
- The CT-AI would learn about the special demands for the test infrastructure to support the testing of AI-based systems.
- Understand how AI can be used to support software testing.
What Is the CT-AI Exam Structure?
The CT-AI exam is a 40 questions long multiple-choice question, where you need to score 31 to pass the exam. You will get one hour time to take the exam.
How Should You Prepare for the CT-AI Exam?
Make Your Syllabus Completion Strategy:
The first thing to succeed in the CT-AI exam is to grasp the syllabus domains. Therefore, go through the topics and make a plan that helps you to cover the syllabus domains from the core. The syllabus covers the following domains-
- Introduction to AI
- Quality Characteristics for AI-Based Systems
- Methods and Techniques for the Testing of AI-Based Systems
- Testing AI-Specific Quality Characteristics
- Testing AI-Based Systems Overview
- ML – Neural Networks and Testing
- ML Functional Performance Metrics
- ML – Data
- Machine Learning (ML)
- Using AI for Testing
- Test Environments for AI-Based Systems
Stay Devoted to Your Study Plan:
Only making the plan is not enough; you must follow it rigorously to earn success. Therefore, focus on studying for at least two to three hours daily and covering a few topics. Make a habit of learning and making notes to utilize during revision.
Practice More to Improve Your Score:
When you face multiple-choice exams, it is essential to become familiar with the exam structure. Therefore, enroll for valuable practice tests and improve your score in the CT-AI exam. You can get valuable insights through these practice tests that help you improve your score in the exam.
What Is AI-Testing?
AI testing comprises tools for automated software testing that leverage AI, usually machine learning to generate better results.
The idea is to help with help those tools overcome many of the common hurdles of automated software testing. AI tools can help to solve common problems-
- duplicated efforts in testing
- insufficient test coverage
- slow execution of tests
- excessive test maintenance due to a fragile test suite
- Create high-quality test cases
The common thing for all tools and approaches is that AI testing tends to optimize automated testing. AI tools help to do that by cutting down or completely removing obstacles in the way of an even more effective test strategy.
What Are the Benefits of Using AI-Testing?
Slow Test Execution Is Solved with AI:
Suppose test suits are running slowly; that creates a problem for the user. AI tools can overcome these challenges.
- AI tools can optimize your test data management strategy, ensuring quality data reaches test cases faster.
- AI tools can figure out only the bare minimum of tests that need to be taken after a given change in the codebase.
- Finally, they might be able to look for unnecessary/duplicated test cases, forgoing their execution.
Excessive Test Maintenance:
Web apps can change frequently and can create a problem. Fragile may break easily with any change to the codebase, especially when identifiers of elements on the page, such as the CSS class of a button, change, and the test tool can no longer find the elements.
An AI-powered tool like Testim Automate can solve that by using machine learning to create sophisticated energy for locating elements on the page, which results in more robust tests.
Creation of High-Quality Test Cases:
AI Test automation tools can help to create well-designed tests by making existing, reusable components that can be called rather than duplicated.
ISTQB and its certifications are trusted across the globe. Therefore, earn the CT-AI certification and strengthen your AI testing career. Become an ISTQB-certified Tester and make yourself globally strong for career advancement.