CT-AI_v1.0_World Exam: Absolutely Free Online Practice

Question 1
- Which of the following neural network coverage criteria can be adapted for its application? Choose ONE option (1 out of 4)
  A : Sign–Sign coverage
  
  B : Sign–Change coverage
  
  C : Threshold coverage
  
  D : Neuron coverage
  
  Answer: C
Question 2
- Which of the following descriptions of quality aspects of a data set is correct? Choose ONE option (1 out of 4)
  A : The quality aspect "Incomplete data" describes the fact that data is missing, e.g., for a certain time interval.
  
  B : The quality aspect "Data not preprocessed" describes the fact that the collected data was recorded incorrectly.
  
  C : The quality aspect "Irrelevant data" describes the fact that irrelevant data does not affect the ML model.
  
  D : The quality aspect "Unbalanced data" describes the fact that the data used should be as up-to-date as possible.
  
  Answer: A
Question 3
- A startup company has implemented a new facial recognition system for a banking application for mobile devices. The application is intended to learn at run-time on the device to determine if the user should be granted access. It also sends feedback over the Internet to the application developers. The application deployment resulted in continuous restarts of the mobile devices. Which of the following is the most likely cause of the failure?
  A : The feedback requires a physical connection and cannot be sent over the Internet.
  
  B : Mobile operating systems cannot process machine learning algorithms.
  
  C : The size of the application is consuming too much of the phone-s storage capacity.
  
  D : The training, processing, and diagnostic generation are too computationally intensive for the mobile device hardware to handle.
  
  Answer: D
Question 4
- A transportation company operates three types of delivery vehicles in its fleet. The vehicles operate at different speeds (slow, medium, and fast). The transportation company is attempting to optimize scheduling and has created an AI-based program to plan routes for its vehicles using records from the medium-speed vehicle traveling to selected destinations. The test team uses this data in metamorphic testing to test the accuracy of the estimated travel times created by the AI route planner with the actual routes and times. Which of the following describes the next phase of metamorphic testing?
  
  A :
  The team tests the time required for the fast and slow vehicles to travel the same route as the medium vehicle. Then, by calculating the speed difference, they then predict how much faster or slower the vehicles will travel. That information is then used to verify that the arrival time of the vehicles meets the expected result.
  
  B :
  The team decomposes each route into the relevant components that affect the travel time such as traffic density and vehicle power. The team then uses statistical analysis to characterize the influence of each component to calculate the fast and slow vehicle route times.
  
  C :
  The team uses an AI system to select the most dissimilar routes. With this information, any of the AI routes can be metaphorically transformed into a fast or slow route.
  
  D :
  The team uses the same AI route planner to create routes that are longer and shorter but follow the same track. Finally, by driving the fast vehicles on the long routes and slow vehicles on the short routes and vice versa, the AI system will have enough information to infer travel times for all vehicles on all routes.
  
  Answer: A
Question 5
- Which machine learning approach is most suitable for predicting customer purchase probability? Choose ONE option (1 out of 4)
  A : Supervised learning (regression)
  
  B : Supervised learning (classification)
  
  C : Unsupervised learning
  
  D : Reinforcement learning
  
  Answer: B

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