[Feb 22, 2023] Free APMG-International Artificial-Intelligence-Foundation Exam Questions & Answer [Q16-Q34]

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[Feb 22, 2023] Free APMG-International Artificial-Intelligence-Foundation Exam Questions and Answer

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NEW QUESTION 16
A human manipulates what using their intelligence?

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

Answer: C

Explanation:
Explanation
Humans use their intelligence to manipulate their environment in order to achieve their objectives and complete their mission. This can involve a wide range of activities, such as building tools, constructing shelters, and creating strategies to solve problems. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/ai/certificate/ and APMG International, https://www.apmg-international.com/qualifications/artificial-intelligence-foundation-certificate.

 

NEW QUESTION 17
Which of the following is an example of fitting a curve to a set of data?

  • A. Bayesian network.
  • B. Backward propagation.
  • C. Python.
  • D. Least squares regression.

Answer: D

Explanation:
Explanation
Least Squares Regression is a statistical technique used for fitting a curve to a set of data. It involves minimizing the sum of the squares of the differences between the observed data and the fitted curve. This is done by finding the line of best fit, which is the line that minimizes the sum of the squared residuals. The line of best fit is determined by finding the parameters that give the minimum sum of the squared residuals. This technique is often used in data science and machine learning to create models that can be used to make predictions. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

 

NEW QUESTION 18
Professor David Chalmers described consciousness as having two questions. What were these?

  • A. An easy one and a hard one.
  • B. What is the sub conscious and what is the conscious?
  • C. Can we integrate our knowledge to form consciousness and can we simulate consciousness?
  • D. Are only humans conscious and are machines always unconscious?

Answer: B

Explanation:
Explanation
Professor David Chalmers described consciousness as having two questions: "What is it like to be conscious?" and "Can machines be conscious?". The first question, "What is it like to be conscious?", is an attempt to understand what it is like to experience the subjective aspects of consciousness, such as feeling, emotion, and perception. The second question, "Can machines be conscious?", is an attempt to understand whether or not machines can have the same kinds of subjective experiences as humans. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.

 

NEW QUESTION 19
If Al undertakes routine and monotonous tasks and takes these away from humans, what will humans do?

  • A. Leisure activities
  • B. Higher value work.
  • C. Sabotage the Al.
  • D. Change jobs.

Answer: B

Explanation:
Explanation
Al is designed to take on routine and monotonous tasks, freeing up humans to take on more complex, higher value work. This can include tasks such as research, problem-solving, and decision-making. This shift in work roles is expected to increase productivity and efficiency, allowing humans to focus on more creative and innovative tasks. For example, robots can be used to automate mundane manufacturing processes, freeing up human workers to take on jobs that require more creative thinking and problem-solving.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international

 

NEW QUESTION 20
Para View allows large data sets to be visualised on a parallel computer.
Which of the following is one of the techniques used?

  • A. Norm calculation.
  • B. Dashboard.
  • C. Eigen function analysis.
  • D. Contour plot

Answer: D

Explanation:
Explanation
ParaView is an open-source, multi-platform visualization application that allows large data sets to be visualized on a parallel computer. ParaView uses a variety of techniques to visualize data, including contour plots, which are useful for visualizing 3D data sets. Contour plots are created by plotting a set of curves connecting points of equal value, with each curve representing a particular value. This allows 3D data sets to be visualized in a 2D format, making it easier to understand the data.
References: [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, Page number 19 [2] APMG International, "What is ParaView?", https://apmg-international.com/en/blog/what-is-paraview/ [3] EXIN,
"What is ParaView?", https://www.exin.com/blog/what-is-paraview/

 

NEW QUESTION 21
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?

  • A. Big Data learning.
  • B. Batch learning.
  • C. Online learning.
  • D. Patchwork learning.

Answer: C

Explanation:
Explanation

Online learning is a type of machine learning that can be used when a large dataset is limited in computational resources or if the data is frequently changing. It allows the system to learn from new data as it is being presented, rather than having to re-train the entire dataset each time new data is added. This makes it more efficient and effective than batch learning, as it only needs to process the new data and not the entire dataset.
Online learning is often used in applications such as fraud detection, where new data is constantly being added and needs to be analyzed quickly.
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 22
What function is used in a Neural Network?

  • A. Trigonometric.
  • B. Statistical.
  • C. Linear.
  • D. Activation.

Answer: D

Explanation:
Explanation
Activation Functions
An activation function in a neural network defines how the weighted sum of the input is transformed into an output from a node or nodes in a layer of the network.
https://machinelearningmastery.com/choose-an-activation-function-for-deep-learning/#:~:text=An%20activation An activation function is a mathematical function used in a neural network to determine the output of a neuron. Activation functions are used to transform the inputs into an output signal and can range from simple linear functions to complex non-linear functions. Activation functions are an important part of neural networks and help the network learn patterns and generalize data. Types of activation functions include sigmoid, ReLU, tanh, and softmax. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/

 

NEW QUESTION 23
The Scrum Master is part of which team?

  • A. Data preparation team
  • B. Agile project team.
  • C. Software development team.
  • D. Management team

Answer: B

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 24
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)

  • A. The central limit
  • B. Kolmogorov's
  • C. Boltzmann's
  • D. Bayes'

Answer: D

Explanation:
Explanation
The development of statistics in the 1800s led to the development of the Bayes' theorem, named after Reverend Thomas Bayes. This theorem is used in probabilistic inference, which is the process of using data to calculate the likelihood of a hypothesis or outcome. The theorem is used for determining the probability of an event occurring given its prior probability, as well as its associated conditions. The Bayes' theorem is also used in a variety of fields, such as machine learning, artificial intelligence, economics, and medical research.
Sources:
* BCS Foundation Certificate In Artificial Intelligence Study Guide: https://www.bcs.org/category/18071
* APMG
International: https://www.apmg-international.com/en/qualifications/qualification-resources/bcs-foundatio
* EXIN: https://www.exin.com/en/certification/bcs-foundation-certificate-in-artificial-intelligence

 

NEW QUESTION 25
Splitting data into Training and Test data sets is part of what?

  • A. Machine learning data preparation.
  • B. Machine learning post processing.
  • C. Batch learning.
  • D. High performance computing strategy.

Answer: A

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 26
In Machine learning what are a brain's axons called?

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

Answer: C

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 27
What does Prof David Chalmers describe the hard consciousness problem to be as comples as?

  • A. The universe.
  • B. Quantum mechanics.
  • C. Psychology.
  • D. Turbulence.

Answer: A

Explanation:
Explanation
Prof David Chalmers describes the hard consciousness problem to be as complex as the universe. He argues that understanding consciousness is as hard as understanding the universe itself, due to the number of variables and dimensions involved. He has compared the complexity of the problem to that of turbulence, quantum mechanics, and psychology, but believes that the problem of consciousness is even more complex than all of these.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
David J. Chalmers, "The Hard Problem of Consciousness", in J. Shear (ed.), Explaining Consciousness: The "Hard Problem", MIT Press, 1997.

 

NEW QUESTION 28
What does TRL stand for?

  • A. Technology Readiness Level.
  • B. Transform Reinforced Learning
  • C. Transport Ready Level.
  • D. Technical Robotic Level.

Answer: A

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 TRL stands for Technology Readiness Level and is a measure of how close a technology is to being ready for use in a real-world environment. TRL is used to assess the progress of research and development of a technology, ranging from basic research (TRL 1) to fully operational (TRL 9). TRL is used to help determine the level of completion of a technology and its potential success in a real-world environment.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international

 

NEW QUESTION 29
What is defined as a machine that can carry out a complex series of tasks automatically?

  • A. An autonomous vehicle.
  • B. A production line.
  • C. A robot
  • D. A computer.

Answer: D

Explanation:
Explanation
https://en.wikipedia.org/wiki/Robot#:~:text=A%20robot%20is%20a%20machine,control%20may%20be%20em A computer is defined as a machine that can carry out a complex series of tasks automatically. Computers are used in a variety of applications, including artificial intelligence (AI), robotics, production lines, and autonomous vehicles. Computers are able to carry out complex tasks thanks to their ability to process large amounts of data quickly and accurately.
For more information, please refer to the BCS Foundation Certificate in Artificial Intelligence Study Guide: https://www.bcs.org/category/18076/bcs-foundation-certificate-in-artificial-intelligence-study-guide.

 

NEW QUESTION 30
How could machine learning make a robot autonomous?

  • A. Use NLP (Natural Language Processing) to listen
  • B. Use actuators to modify its environment
  • C. Learn from sensor data and plan to carry out a task.
  • D. Use OCR, optical character recognition, to read documents

Answer: C

Explanation:
Explanation
Machine learning can be used to make robots autonomous by allowing them to learn from sensor data and plan how to carry out a task. This involves using algorithms to analyze data from sensors and use this data to make decisions and take actions. By using machine learning, robots can learn from their environment and become more autonomous. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Robotics", p.98. [2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"

 

NEW QUESTION 31
What is an intelligent robot?

  • A. A robot that acts like a human.
  • B. A robot that uses Al techniques.
  • C. A robot that has consciousness
  • D. A robot that takes the place of a human.

Answer: B

Explanation:
Explanation
An intelligent robot is one that uses AI techniques, such as machine learning and natural language processing, to perceive, plan and act on its environment. Intelligent robots are able to process large amounts of data quickly and accurately, allowing them to make decisions and carry out tasks autonomously. Intelligent robots can be used in a variety of applications, from industrial automation to healthcare.

 

NEW QUESTION 32
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