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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

SectionObjectives
Topic 1: Machine Learning- ML Fundamentals
  • 1. Supervised and Unsupervised Learning
  • 2. Machine Learning Overview
  • 3. Training and Validation
Topic 2: Testing AI-Based Systems Overview- AI Testing Fundamentals
  • 1. Test Strategy
  • 2. Risk-Based Testing
  • 3. AI Test Lifecycle
Topic 3: Testing AI-Specific Quality Characteristics- Quality Validation
  • 1. Fairness Testing
  • 2. Robustness Testing
  • 3. Explainability Assessment
Topic 4: Quality Characteristics for AI-Based Systems- AI-Specific Quality Attributes
  • 1. Bias
  • 2. Ethics
  • 3. Transparency and Explainability
  • 4. Autonomy
  • 5. Flexibility and Adaptability
  • 6. Evolution
Topic 5: ML Neural Networks and Testing- Neural Networks
  • 1. Neural Network Basics
  • 2. Testing Neural Networks
Topic 6: Methods and Techniques for Testing AI-Based Systems- Test Design Techniques
  • 1. Scenario-Based Testing
  • 2. Data-Oriented Testing
  • 3. Model Testing
Topic 7: ML Functional Performance Metrics- Performance Evaluation
  • 1. Precision
  • 2. Recall
  • 3. Accuracy
  • 4. F1 Score
Topic 8: ML Data- Data Quality
  • 1. Data Preparation
  • 2. Data Collection
  • 3. Data Bias
Topic 9: Introduction to AI- AI Fundamentals
  • 1. AI as a Service
  • 2. AI Technologies
  • 3. AI Definitions and Concepts
  • 4. AI Development Frameworks
  • 5. AI-Based vs Conventional Systems
Topic 10: Using AI for Testing- AI-Assisted Testing
  • 1. Test Data Generation
  • 2. Test Automation Support
  • 3. Defect Prediction
Topic 11: Test Environments for AI-Based Systems- AI Test Infrastructure
  • 1. Data Management
  • 2. Monitoring and Maintenance
  • 3. Environment Configuration

ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

1. ln the near future, technology will have evolved, and Al will be able to learn multiple tasks by itself without needing to be retrained, allowing it to operate even in new environments. The cognitive abilities of Al are similar to a child of 1-2 years.' In the above quote, which ONE of the following options is the correct name of this type of Al?
SELECT ONE OPTION

A) General Al
B) Technological singularity
C) Super Al
D) Narrow Al


2. 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) Non-determinism
C) Self-learning
D) High complexity


3. "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 fast pace of change did not allow sufficient time for testing.
C) There was an algorithmic bias in the Al system.
D) The difficulty of defining criteria for improvement before the model can be accepted.


4. Which ONE of the following models BEST describes a way to model defect prediction by looking at the history of bugs in modules by using code quality metrics of modules of historical versions as input?
SELECT ONE OPTION

A) Using a classification model to predict the presence of a defect by using code quality metrics as the input data.
B) Clustering of similar code modules to predict based on similarity.
C) Identifying the relationship between developers and the modules developed by them.
D) Search of similar code based on natural language processing.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: A
Question # 3
Answer: D
Question # 4
Answer: A

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