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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| Using AI for Testing Activities | 10% | - Regression optimization, test analysis - Test case generation, defect prediction |
| Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| Quality Characteristics for AI-Based Systems | 10% | - Flexibility, adaptability, autonomy - Ethics, bias, transparency and safety |
| ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
| 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 |
| 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. 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 activation values of neurons in the previous layer.
B) Individual bias at the neuron level, and weights assigned to the connections between theneurons.
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.
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) Reinforcement learning
B) Clustering
C) Regression
D) Classification
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) Evaluating the model
C) Data testing
D) Tuning the model
4. Which ONE of the following approaches to labelling requires the least time and effort?
SELECT ONE OPTION
A) Al-Assisted
B) Outsourced
C) Internal
D) Pre-labeled dataset
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: D |

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