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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Introduction to AI | 10% | - AI technologies and frameworks
|
| Topic 2: Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| Topic 3: Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Topic 4: Testing AI-Based Systems | 11% | - Test strategy and approach - Specific challenges and risks |
| Topic 5: Machine Learning (ML) Overview | 11% | - Supervised, unsupervised, reinforcement learning - ML workflow, overfitting, underfitting |
| Topic 6: ML Data | 10% | - Data quality issues and impact - Data acquisition, preprocessing, labeling |
| Topic 7: Using AI for Testing Activities | 10% | - Regression optimization, test analysis - Test case generation, defect prediction |
| Topic 8: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 9: AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Topic 10: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Topic 11: ML Functional Performance Metrics | 11% | - Confusion matrix, accuracy, precision, recall - ROC, AUC, MSE, silhouette coefficient |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
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
- A. This is an example of hyperparameter bias.
- B. This is an example of expert system bias.
- C. This is an example of sample bias.
- D. This is an example of algorithmic bias.
Correct Answer: C 🗳️
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Which ONE of the following describes a situation of back-to-back testing the LEAST?
SELECT ONE OPTION
- A. Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.
- B. Comparison of the results of a home-grown neural network model ML model with results in a neural network model implemented in a standard implementation (for example Pytorch) for same data
- C. Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.
- D. Comparison of the results of a current neural network model ML model implemented in platform A (for example Pytorch) with a similar neural network model ML model implemented in platform B (for example Tensorflow), for the same data.
Correct Answer: A 🗳️
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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
- A. I and III
- B. Only III
- C. I and II
- D. Only II
Correct Answer: C 🗳️
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Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION
- A. Testing the API of the service powered by the ML model.
- B. Testing the accuracy of the classification model.
- C. Testing the speed of the training of the model.
- D. Testing the speed of the prediction by the model.
Correct Answer: C 🗳️
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