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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| ML Neural Networks and Testing | - Neural Networks
|
| Quality Characteristics for AI-Based Systems | - AI-Specific Quality Attributes
|
| Testing AI-Based Systems Overview | - AI Testing Fundamentals
|
| ML Data | - Data Quality
|
| Testing AI-Specific Quality Characteristics | - Quality Validation
|
| Test Environments for AI-Based Systems | - AI Test Infrastructure
|
| Machine Learning | - ML Fundamentals
|
| Methods and Techniques for Testing AI-Based Systems | - Test Design Techniques
|
| Introduction to AI | - AI Fundamentals
|
| ML Functional Performance Metrics | - Performance Evaluation
|
| Using AI for Testing | - AI-Assisted Testing
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
1. Data used for an object detection ML system was found to have been labelled incorrectly in many cases.
Which ONE of the following options is most likely the reason for this problem?
SELECT ONE OPTION
A) Bias issues
B) Privacy issues
C) Security issues
D) Accuracy issues
2. Which ONE of the following statements is a CORRECT adversarial example in the context of machine learning systems that are working on image classifiers.
SELECT ONE OPTION
A) Black box attacks based on adversarial examples create an exact duplicate model of the original.
B) These examples are model specific and are not likely to cause another model trained on same task to fail.
C) These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
D) These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.
3. Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION
A) Testing the speed of the training of the model.
B) Testing the accuracy of the classification model.
C) Testing the API of the service powered by the ML model.
D) Testing the speed of the prediction by the model.
4. Which ONE of the following hardware is MOST suitable for implementing Al when using ML?
SELECT ONE OPTION
A) 64-bit CPUs.
B) Hardware supporting fast matrix multiplication.
C) Hardware supporting high precision floating point operations.
D) High powered CPUs.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: B |
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