AIF Test Pattern, AIF Dumps Questions

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The BCS AIF Certification Exam covers a wide range of topics related to AI, including the history and evolution of AI, machine learning, natural language processing, robotics, and cognitive computing. The exam is designed to assess an individual’s understanding of these topics and their ability to apply them in real-world scenarios. The exam consists of multiple-choice questions and is conducted online. The duration of the exam is one hour, and candidates must achieve a passing score of 65% to obtain the certification.

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BCS Foundation Certificate In Artificial Intelligence Sample Questions (Q13-Q18):

NEW QUESTION # 13
Collaboration, learning and iterative are terms used to describe what?

  • A. Rapid software development.
  • B. Agile projects
  • C. Trustworthy Al.
  • D. Waterfall projects.

Answer: B

Explanation:
Explanation
Collaboration, learning, and iterative are terms used to describe agile projects. Agile projects are designed to be adaptive and flexible, allowing teams to incorporate feedback and learn from their mistakes. This process encourages collaboration between team members, and emphasizes the importance of iterative development and continual improvement. Agile projects focus on delivering value quickly and efficiently, allowing teams to make changes and adapt to changing customer needs.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international

NEW QUESTION # 14
A human manipulates what using their intelligence?

  • A. Space
  • B. Mission
  • C. Objective
  • D. Environment

Answer: A

NEW QUESTION # 15
What term do computer scientists and economists use to describe how happy an agent is?

  • A. Utility.
  • B. Warm.
  • C. Index.
  • D. Return

Answer: A

Explanation:
Explanation
https://griffinshare.fontbonne.edu/cgi/viewcontent.cgi?article=1008&context=ijds

NEW QUESTION # 16
In Machine learning what are a brain’s axons called?

  • A. Nodes
  • B. Dendrites
  • C. Tetrahedra.
  • D. Edges

Answer: A

Explanation:
Explanation
In Machine Learning, the brain’s axons are referred to as nodes. Nodes are the components of a neural network that are responsible for processing the input data and generating the output. A node is a mathematical function that takes input data, performs a computation on it, and produces an output. Each node is connected to other nodes in the network via edges, which represent the strength of the connection between the respective nodes. The strength of the connection between two nodes is determined by the weights assigned to each edge.
The weights are adjusted during the training process to generate the desired results.
For more information, please refer to the BCS Foundation Certificate In Artificial Intelligence Study Guide (https://www.bcs.org/upload/pdf/bcs-foundation-certificate-in-artificial-intelligence-study-guide.pdf) or the EXIN Artificial Intelligence Foundation Certification (https://www.exin.com/en/exams/artificial-intelligence-foundation).

NEW QUESTION # 17
An agent based model is a simul-ation of autonomous agents (individual and collective). What can be used to learn from the data generated by the simul-ations?

  • A. A spreadsheet
  • B. Machine Learning.
  • C. Python.
  • D. Paraview.

Answer: A

Explanation:
https://www.pnas.org/doi/10.1073/pnas.082080899

NEW QUESTION # 18
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