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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
Section
Objectives
Test Environments for AI-Based Systems
- AI Test Infrastructure
1. Environment Configuration
2. Monitoring and Maintenance
3. Data Management
ML Data
- Data Quality
1. Data Collection
2. Data Bias
3. Data Preparation
Methods and Techniques for Testing AI-Based Systems
- Test Design Techniques
1. Data-Oriented Testing
2. Model Testing
3. Scenario-Based Testing
Testing AI-Specific Quality Characteristics
- Quality Validation
1. Explainability Assessment
2. Robustness Testing
3. Fairness Testing
Quality Characteristics for AI-Based Systems
- AI-Specific Quality Attributes
1. Bias
2. Transparency and Explainability
3. Evolution
4. Flexibility and Adaptability
5. Autonomy
6. Ethics
ML Neural Networks and Testing
- Neural Networks
1. Testing Neural Networks
2. Neural Network Basics
Testing AI-Based Systems Overview
- AI Testing Fundamentals
1. Risk-Based Testing
2. Test Strategy
3. AI Test Lifecycle
ML Functional Performance Metrics
- Performance Evaluation
1. Recall
2. Precision
3. Accuracy
4. F1 Score
Using AI for Testing
- AI-Assisted Testing
1. Test Automation Support
2. Test Data Generation
3. Defect Prediction
Introduction to AI
- AI Fundamentals
1. AI as a Service
2. AI-Based vs Conventional Systems
3. AI Development Frameworks
4. AI Definitions and Concepts
5. AI Technologies
Machine Learning
- ML Fundamentals
1. Training and Validation
2. Supervised and Unsupervised Learning
3. Machine Learning Overview
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems? SELECT ONE OPTION
A. Nature of data constantly changes with lime.
B. Data for the use case is being generated at a fast pace.
C. Compliance needs require proper care to be taken of input personal data.
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A system was developed for screening the X-rays of patients for potential malignancy detection (skin cancer). A workflow system has been developed to screen multiple cancers by using several individually trained ML models chained together in the workflow. Testing the pipeline could involve multiple kind of tests (I - III): I.Pairwise testing of combinations II.Testing each individual model for accuracy III.A/B testing of different sequences of models Which ONE of the following options contains the kinds of tests that would be MOST APPROPRIATE to include in the strategy for optimal detection? SELECT ONE OPTION
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Data used for an object detection ML system was found to have been labelled incorrectly in many cases. Which ONE of the following options is most likely the reason for this problem? SELECT ONE OPTION
An image classification system is being trained for classifying faces of humans. The distribution of the data is 70% ethnicity A and 30% for ethnicities B, C and D. Based ONLY on the above information, which of the following options BEST describes the situation of this image classification system? SELECT ONE OPTION
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discussion
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