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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| ML Functional Performance Metrics | 11% | - Confusion matrix, accuracy, precision, recall - ROC, AUC, MSE, silhouette coefficient |
| ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Using AI for Testing Activities | 10% | - Regression optimization, test analysis - Test case generation, defect prediction |
| Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| Introduction to AI | 10% | - AI technologies and frameworks
|
| Quality Characteristics for AI-Based Systems | 10% | - Flexibility, adaptability, autonomy - Ethics, bias, transparency and safety |
| Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
"BioSearch" is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model.
A testing expert was called in to find the deficiencies in the test planning which led to the above scenario.
Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
SELECT ONE OPTION
- A. A lack of focus on non-functional requirements testing.
- B. A lack of focus on choosing the right functional-performance metrics.
- C. The input data has not been tested for quality prior to use for testing.
- D. A lack of similarity between the training and testing data.
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Max. Score: 2
Al-enabled medical devices are used nowadays for automating certain parts of the medical diagnostic processes. Since these are life-critical process the relevant authorities are considenng bringing about suitable certifications for these Al enabled medical devices. This certification may involve several facets of Al testing (I - V).
I.Autonomy
II.Maintainability
III.Safety
IV.Transparency
V.Side Effects
Which ONE of the following options contains the three MOST required aspects to be satisfied for the above scenario of certification of Al enabled medical devices?
SELECT ONE OPTION
- A. Aspects III, IV, and V
- B. Aspects I, II, and III
- C. Aspects II, III and IV
- D. Aspects I, IV, and V
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In a certain coffee producing region of Colombia, there have been some severe weather storms, resulting in massive losses in production. This caused a massive drop in stock price of coffee.
Which ONE of the following types of testing SHOULD be performed for a machine learning model for stock-price prediction to detect influence of such phenomenon as above on price of coffee stock.
SELECT ONE OPTION
- A. Testing for accuracy
- B. Testing for security
- C. Testing for bias
- D. Testing for concept drift
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Which ONE of the following statements correctly describes the importance of flexibility for Al systems?
SELECT ONE OPTION
- A. Self-learning systems are expected to deal with new situations without explicitly having to program for it.
- B. Al systems require changing of operational environments; therefore, flexibility is required.
- C. Al systems are inherently flexible.
- D. Flexible Al systems allow for easier modification of the system as a whole.
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