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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: ML Functional Performance Metrics | 11% | - Confusion matrix, accuracy, precision, recall - ROC, AUC, MSE, silhouette coefficient |
| Topic 2: Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Topic 3: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Topic 4: Introduction to AI | 10% | - AI technologies and frameworks
|
| Topic 5: Machine Learning (ML) Overview | 11% | - ML workflow, overfitting, underfitting - Supervised, unsupervised, reinforcement learning |
| Topic 6: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 7: Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| Topic 8: ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Topic 9: AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Topic 10: Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| Topic 11: Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
1. 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) Classification
B) Regression
C) Reinforcement learning
D) Clustering
2. Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements?
SELECT ONE OPTION
A) Analyzing source code for generating test cases
B) GUI analysis by computer vision
C) Machine learning on logs of execution
D) Natural language processing on textual requirements
3. Upon testing a model used to detect rotten tomatoes, the following data was observed by the test engineer, based on certain number of tomato images.
For this confusion matrix which combinations of values of accuracy, recall, and specificity respectively is CORRECT?
SELECT ONE OPTION
A) 0.84.1,0.9
B) 1,0.87,0.84
C) 0.87.0.9. 0.84
D) 1,0.9, 0.8
4. An image classification system is being trained for classifying faces of humans. The distribution of the data is
70% ethnicity A and 30% for ethnicities B, C and D. Based ONLY on the above information, which of the following options BEST describes the situation of this image classification system?
SELECT ONE OPTION
A) This is an example of expert system bias.
B) This is an example of algorithmic bias.
C) This is an example of hyperparameter bias.
D) This is an example of sample bias.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: D |
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