Exam Name: ISTQB Certified Tester AI Testing (v1.0)
Certification Provider: ISQI
Corresponding Certification: AI Testing
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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Methods and Techniques for Testing AI-Based Systems | - Test Design Techniques
|
| Introduction to AI | - AI Fundamentals
|
| Quality Characteristics for AI-Based Systems | - AI-Specific Quality Attributes
|
| Machine Learning | - ML Fundamentals
|
| Test Environments for AI-Based Systems | - AI Test Infrastructure
|
| ML Functional Performance Metrics | - Performance Evaluation
|
| Testing AI-Based Systems Overview | - AI Testing Fundamentals
|
| ML Data | - Data Quality
|
| Using AI for Testing | - AI-Assisted Testing
|
| Testing AI-Specific Quality Characteristics | - Quality Validation
|
| ML Neural Networks and Testing | - Neural Networks
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
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. Identifying suitable tests by looking at the complexity of the test cases.
- B. Automating test scripts using Al-based test automation tools.
- C. Using of a random subset of tests.
- D. Using an Al-based tool to optimize the regression test suite by analyzing past test results
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A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.
Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
SELECT ONE OPTION
- A. Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.
- B. Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.
- C. Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
- D. Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Which ONE of the following characteristics is the least likely to cause safety related issues for an Al system?
SELECT ONE OPTION
- A. Robustness
- B. Self-learning
- C. High complexity
- D. Non-determinism
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.
Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?
SELECT ONE OPTION
- A. Different features like ADAS, Lane Change Assistance etc.
- B. Different Road Types
- C. Different weather conditions
- D. ML model metrics to evaluate the functional performance
Explanation: Only visible for Prep4away members. You can sign-up / login (it's free).
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