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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 AI-Based Systems | 11% | - Test strategy and approach - Specific challenges and risks |
| Topic 3: Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Topic 4: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 5: ML Data | 10% | - Data quality issues and impact - Data acquisition, preprocessing, labeling |
| Topic 6: ML Functional Performance Metrics | 11% | - Confusion matrix, accuracy, precision, recall - ROC, AUC, MSE, silhouette coefficient |
| Topic 7: Machine Learning (ML) Overview | 11% | - Supervised, unsupervised, reinforcement learning - ML workflow, overfitting, underfitting |
| Topic 8: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Topic 9: AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Topic 10: Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| 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:
1. Which of the following is THE LEAST appropriate tests to be performed for testing a feature related to autonomy?
SELECT ONE OPTION
A) Test for human handover when it should actually not be relinquishing control.
B) Test for human handover requiring mandatory relinquishing control.
C) Test for human handover to give rest to the system.
D) Test for human handover after a given time interval.
2. Which ONE of the following models BEST describes a way to model defect prediction by looking at the history of bugs in modules by using code quality metrics of modules of historical versions as input?
SELECT ONE OPTION
A) Using a classification model to predict the presence of a defect by using code quality metrics as the input data.
B) Clustering of similar code modules to predict based on similarity.
C) Identifying the relationship between developers and the modules developed by them.
D) Search of similar code based on natural language processing.
3. The activation value output for a neuron in a neural network is obtained by applying computation to the neuron.
Which ONE of the following options BEST describes the inputs used to compute the activation value?
SELECT ONE OPTION
A) Individual bias at the neuron level, and weights assigned to the connections between theneurons.
B) Individual bias at the neuron level, and activation values of neurons in the previous layer.
C) Activation values of neurons in the previous layer, and weights assigned to the connections between the neurons.
D) Individual bias at the neuron level, activation values of neurons in the previous layer, and weights assigned to the connections between the neurons.
4. Which ONE of the following options does NOT describe an Al technology related characteristic which differentiates Al test environments from other test environments?
SELECT ONE OPTION
A) Challenges in the creation of scenarios of human handover for autonomous systems.
B) The challenge of providing explainability to the decisions made by the system.
C) The challenge of mimicking undefined scenarios generated due to self-learning
D) Challenges resulting from low accuracy of the models.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: A |
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