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BCS Foundation Certificate In Artificial Intelligence Sample Questions (Q13-Q18):
NEW QUESTION # 13
What does TRL stand for?
- A. Transport Ready Level.
- B. Technology Readiness Level.
- C. Technical Robotic Level.
- D. Transform Reinforced Learning
Answer: B
Explanation:
Explanation
Technology Readiness Level (TRL) Technology Readiness Levels (TRL) are a method of estimating the
technology maturity of Critical Technology Elements (CTE) of a program during the acquisition process.
https://acqnotes.com/acqnote/tasks/technology-readiness-level#:~:text=Technology%20Development-,Technolog
NEW QUESTION # 14
What is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a
class of problems?
- A. A set
- B. An approach.
- C. A paradigm.
- D. An algorithm.
Answer: C
NEW QUESTION # 15
Which of the following is an example of fitting a curve to a set of data?
- A. Bayesian network.
- B. Python.
- C. Backward propagation.
- D. Least squares regression.
Answer: D
NEW QUESTION # 16
The Scrum Master is part of which team?
- A. Software development team.
- B. Data preparation team
- C. Management team
- D. Agile project team.
Answer: D
Explanation:
Explanation
https://www.techtarget.com/whatis/definition/scrum-master#:~:text=A%20Scrum%20Master%20is%20a,in%20a The Scrum Master is part of the agile project team, and is responsible for ensuring that the team is following the Scrum process. The Scrum Master is the facilitator of the team, ensuring that the team is working together and following the Scrum principles. They are also responsible for protecting the team from any external influences and helping resolve any issues that may arise.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 17
Splitting data into Training and Test data sets is part of what?
- A. High performance computing strategy.
- B. Batch learning.
- C. Machine learning post processing.
- D. Machine learning data preparation.
Answer: D
Explanation:
Explanation
Splitting data into training and test data sets is an important step in the machine learning data preparation process. This process involves splitting the data into subsets, usually in a 70:30 ratio, to create a training set and a test set. The training set is used to train the machine learning model, while the test set is used to evaluate the model's performance. This process allows for the model to be tested and evaluated on data that it has not seen before, in order to ensure that it is accurate and able to generalize to new data. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/
NEW QUESTION # 18
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