Development, testing & web - ISTQB® Certified Tester AI Testing (CT-AI) certification
A practical course focused on ISTQB® Certified Tester AI Testing (CT-AI) certification. Participants build skills across three priorities: Introduction to AI, Quality characteristics of AI systems, Overview of Machine Learning (ML).
Detailed programme
Introduction to AI
- Types of AI: narrow, general and super AI AI.
- AI as a service (AiaaS).
- Standards and regulations.
Quality characteristics of AI systems
- Flexibility, adaptability and autonomy.
- Bias, ethics and security in AI.
- Transparency, interpretability and explicability.
Overview of Machine Learning (ML)
- Workflow ML and algorithm selection.
- Over-adjustment, under-adjustment.
ML - Data
- Training, validation and test data sets.
- Data quality problems and effects on ML models.
- Data labelling and approaches.
Functional performance measurements for ML
- Confusion and performance matrix in ML.
- Limitations and test suites for ML models.
ML - Neural networks and tests
- Introduction to neural networks.
- Implementation of a simple perceptron.
- Coverage measures for neural networks.
Test of AI-based systems - Overview
- Specifications and testing levels.
- Test data and approaches.
- Testing automation biases.
Testing the characteristics of AI
- Challenges related to testing autonomous systems.
- Address algorithmic biases and complexity.
- Test complex AI systems.
Methods and techniques for testing AI systems
- Adverse attacks and data poisoning.
- Pair, back-to-back, A/B and metamorphic tests.
- Selection of test techniques.
Test environments for AI systems
- Configuration and considerations for test environments.
- Virtual test environments for AI tests.
Use of AI for testing
- AI technologies for testing.
- AI in defect analysis, generation of test cases.
- AI in fault prediction and IHM tests.
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Our offices
- Exceev Consulting
61 Rue de Lyon
75012, Paris, France - Exceev Technology
332 Bd Brahim Roudani
20330, Casablanca, Morocco