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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning | - ML Fundamentals
|
| Topic 2: Test Environments for AI-Based Systems | - AI Test Infrastructure
|
| Topic 3: Quality Characteristics for AI-Based Systems | - AI-Specific Quality Attributes
|
| Topic 4: ML Data | - Data Quality
|
| Topic 5: Introduction to AI | - AI Fundamentals
|
| Topic 6: Using AI for Testing | - AI-Assisted Testing
|
| Topic 7: Testing AI-Specific Quality Characteristics | - Quality Validation
|
| Topic 8: Methods and Techniques for Testing AI-Based Systems | - Test Design Techniques
|
| Topic 9: ML Neural Networks and Testing | - Neural Networks
|
| Topic 10: ML Functional Performance Metrics | - Performance Evaluation
|
| Topic 11: Testing AI-Based Systems Overview | - AI Testing Fundamentals
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
1. 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) These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
B) These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.
C) Black box attacks based on adversarial examples create an exact duplicate model of the original.
D) These examples are model specific and are not likely to cause another model trained on same task to fail.
2. Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION
A) Testing the API of the service powered by the ML model.
B) Testing the speed of the prediction by the model.
C) Testing the speed of the training of the model.
D) Testing the accuracy of the classification model.
3. 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 resulting from low accuracy of the models.
B) The challenge of mimicking undefined scenarios generated due to self-learning
C) Challenges in the creation of scenarios of human handover for autonomous systems.
D) The challenge of providing explainability to the decisions made by the system.
4. "Splendid Healthcare" has started developing a cancer detection system based on ML. The type of cancer they plan on detecting has 2% prevalence rate in the population of a particular geography. It is required that the model performs well for both normal and cancer patients.
Which ONE of the following combinations requires MAXIMIZATION?
SELECT ONE OPTION
A) Maximize accuracy and recall
B) Maximize precision and accuracy
C) Maximize specificity number of classes
D) Maximize recall and precision
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: D |
Ida 
Eve 
Harley 
Baldwin 
Megan 
Bertram 
Colin 
Selena 
Ziv 
Kenneth 
Leo 
Liz 
Dolores 
Chloe 
