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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| Topic 2: AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| Topic 3: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 4: Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| Topic 5: Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Topic 6: ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
| Topic 7: Introduction to AI | 10% | - AI definitions and types
|
| Topic 8: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Topic 9: Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
| Topic 10: ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Topic 11: Using AI for Testing Activities | 10% | - Regression optimization, test analysis - Test case generation, defect prediction |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
Question #1
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 I, II, and III
B. Aspects III, IV, and V
C. Aspects I, IV, and V
D. Aspects II, III and IV
Question #2
Which ONE of the following describes a situation of back-to-back testing the LEAST?
SELECT ONE OPTION
A. Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.
B. 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.
C. 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
D. Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.
Question #3
Which ONE of the following options is the MOST APPROPRIATE stage of the ML workflow to set model and algorithm hyperparameters?
SELECT ONE OPTION
A. Deploying the model
B. Tuning the model
C. Data testing
D. Evaluating the model
Question #4
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 bias
B. Testing for concept drift
C. Testing for accuracy
D. Testing for security
Solutions:
| Question #1 Answer: B | Question #2 Answer: D | Question #3 Answer: B | Question #4 Answer: B |
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