Description
The Certified Tester AI Testing (CT-AI) qualification is aimed at people who are seeking to extend their understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI based systems and using AI to test.
Individuals who hold the ISTQB® Certified Tester- AI Testing certification should be able to accomplish the following business outcomes:
- Understand the current state and expected trends of AI
- Experience the implementation and testing of a ML model and recognize where testers can best influence its quality
- Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability
- Contribute to the test strategy for an AI-Based system
- Design and execute test cases for AI-based systems
- Recognize the special requirements for the test infrastructure to support the testing of AI-based systems
- Understand how AI can be used to support software testing
Chapter 1: Introduction to AI
Chapter 2: Quality Characteristics for AI-Based Systems
Chapter 3: Machine Learning (ML)
Chapter 4: ML - Data
Chapter 5: ML Functional Performance Metrics
Chapter 6: ML - Neural Networks and Testing
Chapter 7: Testing AI-Based Systems Overview
Chapter 8: Testing AI-Specific Quality Characteristics
Chapter 9: Methods and Techniques for the Testing of AI-Based Systems
Chapter 10: Test Environments for AI-Based Systems
Chapter 11: Using AI for Testing
Target Audience
The Certified Tester AI Testing (CT-AI) qualification is aimed at people who are seeking to extend their understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI based systems and using AI to test.
Requirements
- Have successfully passed the ISTQB® CTFL Certification exam and hold the certificate.
- First experience in AI projects is recommended, but not required.
The global exam price vary depending on the certification and your geographical location.
