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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Introduction to AI | 10% | - AI definitions and types
|
| AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| Machine Learning (ML) Overview | 11% | - Supervised, unsupervised, reinforcement learning - ML workflow, overfitting, underfitting |
| Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
Which ONE of the following describes a situation of back-to-back testing the LEAST?
SELECT ONE OPTION
- A. 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
- B. Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.
- C. 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.
- D. Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.
Correct Answer: B 🗳️
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Which ONE of the following approaches to labelling requires the least time and effort?
SELECT ONE OPTION
- A. Pre-labeled dataset
- B. Internal
- C. Al-Assisted
- D. Outsourced
Correct Answer: A 🗳️
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Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
SELECT ONE OPTION
- A. Compliance needs require proper care to be taken of input personal data.
- B. Test data being sourced from public sources.
- C. Data for the use case is being generated at a fast pace.
- D. Nature of data constantly changes with lime.
Correct Answer: C 🗳️
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Arihant Meditation is a startup using Al to aid people in deeper and better meditation based on analysis of various factors such as time and duration of the meditation, pulse and blood pressure, EEG patters etc. among others. Their model accuracy and other functional performance parameters have not yet reached their desired level.
Which ONE of the following factors is NOT a factor affecting the ML functional performance?
SELECT ONE OPTION
- A. The data pipeline
- B. Biased data
- C. The number of classes
- D. The quality of the labeling
Correct Answer: C 🗳️
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