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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
| Topic 2: ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
| Topic 3: Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| Topic 4: Introduction to AI | 10% | - AI technologies and frameworks
|
| Topic 5: Neural Networks and Testing | 4% | - Coverage measures for deep learning - Structure of neural networks |
| Topic 6: ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Topic 7: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 8: Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| Topic 9: AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| Topic 10: Testing AI-Based Systems | 11% | - Test strategy and approach - Specific challenges and risks |
| Topic 11: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.
Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?
SELECT ONE OPTION
- A. Different weather conditions
- B. Different features like ADAS, Lane Change Assistance etc.
- C. ML model metrics to evaluate the functional performance
- D. Different Road Types
Correct Answer: C 🗳️
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Which ONE of the following options does NOT describe an Al technology related characteristic which differentiates Al test environments from other test environments?
SELECT ONE OPTION
- A. The challenge of mimicking undefined scenarios generated due to self-learning
- B. Challenges resulting from low accuracy of the models.
- C. Challenges in the creation of scenarios of human handover for autonomous systems.
- D. The challenge of providing explainability to the decisions made by the system.
Correct Answer: C 🗳️
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A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.
Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
SELECT ONE OPTION
- A. Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.
- B. Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
- C. Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.
- D. Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.
Correct Answer: A 🗳️
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Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
SELECT ONE OPTION
- A. Test data being sourced from public sources.
- B. Compliance needs require proper care to be taken of input personal data.
- C. Data for the use case is being generated at a fast pace.
- D. Nature of data constantly changes with lime.
Correct Answer: C 🗳️
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