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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Using AI for Testing | - AI-Assisted Testing
|
| Methods and Techniques for Testing AI-Based Systems | - Test Design Techniques
|
| Testing AI-Specific Quality Characteristics | - Quality Validation
|
| Test Environments for AI-Based Systems | - AI Test Infrastructure
|
| ML Data | - Data Quality
|
| Testing AI-Based Systems Overview | - AI Testing Fundamentals
|
| Machine Learning | - ML Fundamentals
|
| Introduction to AI | - AI Fundamentals
|
| ML Neural Networks and Testing | - Neural Networks
|
| ML Functional Performance Metrics | - Performance Evaluation
|
| Quality Characteristics for AI-Based Systems | - AI-Specific Quality Attributes
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
Which ONE of the following activities is MOST relevant when addressing the scenario where you have more than the required amount of data available for the training?
SELECT ONE OPTION
- A. Data augmentation
- B. Data labeling
- C. Feature selection
- D. Data sampling
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Which ONE of the following is the BEST option to optimize the regression test selection and prevent the regression suite from growing large?
SELECT ONE OPTION
- A. Using an Al-based tool to optimize the regression test suite by analyzing past test results
- B. Automating test scripts using Al-based test automation tools.
- C. Identifying suitable tests by looking at the complexity of the test cases.
- D. Using of a random subset of tests.
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"AllerEgo" is a product that uses sell-learning to predict the behavior of a pilot under combat situation for a variety of terrains and enemy aircraft formations. Post training the model was exposed to the real- world data and the model was found to bebehaving poorly. A lot of data quality tests had been performed on the data to bring it into a shape fit for training and testing.
Which ONE of the following options is least likely to describes the possible reason for the fall in the performance, especially when considering the self-learning nature of the Al system?
SELECT ONE OPTION
- A. The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
- B. The difficulty of defining criteria for improvement before the model can be accepted.
- C. There was an algorithmic bias in the Al system.
- D. The fast pace of change did not allow sufficient time for testing.
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A system was developed for screening the X-rays of patients for potential malignancy detection (skin cancer).
A workflow system has been developed to screen multiple cancers by using several individually trained ML models chained together in the workflow.
Testing the pipeline could involve multiple kind of tests (I - III):
I.Pairwise testing of combinations
II.Testing each individual model for accuracy
III.A/B testing of different sequences of models
Which ONE of the following options contains the kinds of tests that would be MOST APPROPRIATE to include in the strategy for optimal detection?
SELECT ONE OPTION
- A. I and III
- B. I and II
- C. Only II
- D. Only III
Explanation: Only visible for PassCollection members. You can sign-up / login (it's free).
Broderick 
Adela 
James 
Dean 
Virginia 
Sarah 
Armstrong 
Booth 
Xenia 
Marshall 
Egbert 
Aldrich 
Dominic 
