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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Neural Networks and Testing | 4% | - Coverage measures for deep learning - Structure of neural networks |
| Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| ML Functional Performance Metrics | 11% | - Confusion matrix, accuracy, precision, recall - ROC, AUC, MSE, silhouette coefficient |
| Quality Characteristics for AI-Based Systems | 10% | - Flexibility, adaptability, autonomy - Ethics, bias, transparency and safety |
| AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
| Using AI for Testing Activities | 10% | - Regression optimization, test analysis - Test case generation, defect prediction |
| Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Introduction to AI | 10% | - AI technologies and frameworks
|
| ML Data | 10% | - Data quality issues and impact - Data acquisition, preprocessing, labeling |
| Testing AI-Based Systems | 11% | - Test strategy and approach - Specific challenges and risks |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
1. 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 Road Types
B) ML model metrics to evaluate the functional performance
C) Different weather conditions
D) Different features like ADAS, Lane Change Assistance etc.
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) Regression
B) Clustering
C) Reinforcement learning
D) Classification
3. Which ONE of the following types of coverage SHOULD be used if test cases need to cause each neuron to achieve both positive and negative activation values?
SELECT ONE OPTION
A) Sign change coverage
B) Value coverage
C) Neuron coverage
D) Threshold coverage
4. Which ONE of the following is the BEST option to optimize the regression test selection and prevent the regression suite from growing large?
SELECT ONE OPTION
A) Automating test scripts using Al-based test automation tools.
B) Using of a random subset of tests.
C) Identifying suitable tests by looking at the complexity of the test cases.
D) Using an Al-based tool to optimize the regression test suite by analyzing past test results
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: A | Question # 4 Answer: D |
