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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

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

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

1. Which ONE of the following options is the MOST APPROPRIATE stage of the ML workflow to set model and algorithm hyperparameters?
SELECT ONE OPTION

A) Evaluating the model
B) Deploying the model
C) Data testing
D) Tuning the model


2. Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
SELECT ONE OPTION

A) Compliance needs require proper care to be taken of input personal data.
B) Test data being sourced from public sources.
C) Data for the use case is being generated at a fast pace.
D) Nature of data constantly changes with lime.


3. A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?
SELECT ONE OPTION

A) Reinforcement learning
B) Clustering
C) Regression
D) Classification


4. 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) Only II
C) Only III
D) I and II


Solutions:

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

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