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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 |
| Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| Quality Characteristics for AI-Based Systems | 10% | - Flexibility, adaptability, autonomy - Ethics, bias, transparency and safety |
| Neural Networks and Testing | 4% | - Coverage measures for deep learning - Structure of neural networks |
| ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
| Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Introduction to AI | 10% | - AI technologies and frameworks
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
1. "Splendid Healthcare" has started developing a cancer detection system based on ML. The type of cancer they plan on detecting has 2% prevalence rate in the population of a particular geography. It is required that the model performs well for both normal and cancer patients.
Which ONE of the following combinations requires MAXIMIZATION?
SELECT ONE OPTION
A) Maximize specificity number of classes
B) Maximize accuracy and recall
C) Maximize precision and accuracy
D) Maximize recall and precision
2. A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?
SELECT ONE OPTION
A) Clustering
B) Reinforcement learning
C) Regression
D) Classification
3. 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 sample bias.
B) This is an example of expert system bias.
C) This is an example of algorithmic bias.
D) This is an example of hyperparameter bias.
4. 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) Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
B) 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.
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.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: B |
