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Artificial-Intelligence-Foundation Exam with Guarantee Updated 40 Questions
APMG-International Artificial-Intelligence-Foundation certification is designed for professionals who are looking to gain a comprehensive understanding of the principles and practices of artificial intelligence. Foundation Certification Artificial Intelligence certification is highly valued in the industry as it demonstrates that the certified professional has a solid grasp of the foundational concepts of AI. Foundation Certification Artificial Intelligence certification exam is conducted by APMG, an internationally recognized accreditation and examination body.
NEW QUESTION # 24
Which of the following is an example of fitting a curve to a set of data?
- A. Python.
- B. Backward propagation.
- C. Bayesian network.
- 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 # 25
From the Ell's ethics guidelines for Al, what does 'The Principle of Autonomy,' mean?
- A. Robots will have freewill.
- B. Al agents will behave as humans.
- C. Al systems will preserve human agency.
- D. Al systems will be human-centric
Answer: C
Explanation:
Explanation
The Principle of Autonomy from the ELL's ethics guidelines for Al states that Al systems should be designed in a way that preserves human agency and responsibility. This means that Al systems should be designed in a way that allows humans to remain in control of their decisions, and that the Al system should not be able to act without human input or permission. 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 # 26
In an Al project the domain expert is the person...
- A. who manages the agile project and writes the technical terms of reference
- B. who measures the trustworthiness of the Al system
- C. with special knowledge or skills in the area of endeavour and defines what is fit for purpose'
- D. with technical and managerial oversight of the business plan
Answer: C
Explanation:
Explanation
In an AI project, a domain expert is a person with special knowledge or skills in that particular area of endeavour, and they are responsible for defining what is "fit for purpose" for the project. The domain expert provides insights into the problem and suggests ways to address it. They also provide guidance on evaluating and validating the AI system and its outputs. The domain expert is also responsible for communicating with stakeholders and providing feedback on the progress of the project. References:
* BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), AI & People, Chapter 12.
* https://www.apmg-international.com/en/al-adoption/domain-expert/
NEW QUESTION # 27
Ensemble learning methods do what with the hypothesis space?
- A. Use stochastic gradient descent to optimise a network.
- B. Test multiple hypotheses simultaneously.
- C. Extract ergodic solutions.
- D. Select a combination of hypothesis to combine their predictions
Answer: D
Explanation:
Explanation
https://link.springer.com/referenceworkentry/10.1007/978-0-387-73003-5_293#:~:text=Definition,and%20comb It works by selecting different subsets of the data, or different combinations of the hypothesis, and combining the results of each prediction in order to create a single, more accurate result. This is useful in situations where different hypothesis may be accurate in different parts of the data, or where a single hypothesis may not be accurate in all cases. Ensemble learning is used in a variety of applications, from computer vision to natural language processing.
References: [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, BCS [2] Apmg-international.com, "What is Ensemble Learning?", APMG International, https://apmg-international.com/en/about-apmg/blog/what-is-ensemble-learning/ [3] Exin.com,
"Ensemble Learning", EXIN, https://www.exin.com/en-us/learn/ensemble-learning
NEW QUESTION # 28
An intelligent robot uses Al to do what?
- A. Perceive, plan and act.
- B. Sense, plan and act
- C. Sense, plan and move.
- D. Plan, act and speak.
Answer: A
Explanation:
Explanation
An intelligent robot uses Artificial Intelligence (AI) to perceive its environment, plan its actions and then act on them. This is sometimes referred to as the "sense, plan, act" cycle, and is at the heart of what makes a robot intelligent. By using AI, robots can sense their environment, plan their actions accordingly and then act on them in order to complete their tasks.
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 # 29
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 # 30
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. An autonomous vehicle.
- B. A robot
- C. A production line.
- 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 # 31
In Machine learning what are a brain's axons called?
- A. Nodes
- B. Edges
- C. Tetrahedra.
- D. Dendrites
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 # 32
Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?
- A. Autonomous vehicles.
- B. Automated blood sampling.
- C. Diagnostic image analysis
- D. Autonomous wheelchairs.
Answer: C
Explanation:
Explanation
Healthcare can benefit from AI, and in particular Machine Learning, in a number of ways. One example is diagnostic image analysis, which can help to automatically identify and classify abnormalities in medical images such as X-rays, CT scans, and MRI scans. Machine Learning algorithms can be used to detect patterns in the data which can be used to accurately diagnose diseases and illnesses.
References:
[1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf [2] https://www.apmg-international
NEW QUESTION # 33
The EU's Ethical Guidelines use what to demonstrate trustworthy Al?
- A. A quality assurance plan.
- B. UN's sustainability goals.
- C. A human-centric value system.
- D. Customer feedback.
Answer: C
Explanation:
Explanation
The European Union's Ethical Guidelines for Trustworthy AI use a human-centric value system to demonstrate that Artificial Intelligence (AI) is trustworthy. This value system is based on human rights, autonomy, safety, privacy, transparency, accountability and fairness. The guidelines also state that AI should be designed, developed and used in a manner that respects these values. References:
* https://ec.europa.eu/digital-single-market/en/news/ethical-guidelines-trustworthy-ai
* BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), A.I & Ethics, Chapter 5.
NEW QUESTION # 34
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Iteration.
- B. Over-fitting
- C. Activation.
- D. Boosting.
Answer: D
Explanation:
Explanation
* Weak Learner: Colloquially, a model that performs slightly better than a naive model.
More formally, the notion has been generalized to multi-class classification and has a different meaning beyond better than 50 percent accuracy.
For binary classification, it is well known that the exact requirement for weak learners is to be better than random guess. [...] Notice that requiring base learners to be better than random guess is too weak for multi-class problems, yet requiring better than 50% accuracy is too stringent.
- Page 46, Ensemble Methods, 2012.
It is based on formal computational learning theory that proposes a class of learning methods that possess weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as a simplification of the more desirable strong learnability, where a learnable achieved arbitrary good classification accuracy.
A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to achieve arbitrarily high accuracy; a weak learning algorithm needs only output an hypothesis that performs slightly better (by an inverse polynomial) than random guessing.
- The Strength of Weak Learnability, 1990.
It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak learners as opposed to strong, at least in the colloquial meaning of the term.
More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.
The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.
https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble-learning/ The best technique to adopt when a weak learner's hypothesis accuracy is only slightly better than 50% is boosting. Boosting is an ensemble learning technique that combines multiple weak learners (i.e., models with a low accuracy) to create a more powerful model. Boosting works by iteratively learning a series of weak learners, each of which is slightly better than random guessing. The output of each weak learner is then combined to form a more accurate model. Boosting is a powerful technique that has been proven to improve the accuracy of a wide range of machine learning tasks. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
NEW QUESTION # 35
Human-centric trustworthy Al must be...
- A. quality assurance certified.
- B. continually assessed and monitored.
- C. financially sustainable.
- D. tested by humans.
Answer: B
Explanation:
Explanation
Human-centric trustworthy Al must be continually assessed and monitored in order to ensure that it is behaving in a safe and ethical manner. This includes conducting regular tests and audits to ensure that the Al is functioning as intended, and is not taking any actions or decisions that could potentially harm humans or their environment. 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 # 36
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Artificial General Intelligence.
- B. Machine.
- C. Human plus machine.
- D. Human.
Answer: B
Explanation:
Explanation
Monotonous and repetitive tasks that require accuracy are best suited to machines. Machines are able to accurately and quickly perform tasks that require little to no creativity, such as data entry or image recognition.
This is because machines are able to process large amounts of data quickly and accurately, and are less likely to make mistakes than humans. Additionally, machines are able to process large amounts of data without becoming bored or distracted, making them ideal for tasks that require consistent accuracy. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.
Search results: BCS Foundation Certificate in Artificial Intelligence Study Guide, Chapter 4: Machine Learning: https://www.bcs.org/category/19669
NEW QUESTION # 37
A human manipulates what using their intelligence?
- A. Mission
- B. Objective
- C. Environment
- D. Space
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 # 38
Which of the following is an advantage of a machine based system?
- A. Undertakes monotonous tasks reliably and accurately.
- B. Capable of sympathising with humans.
- C. Able to judge ambiguous and unknown situations.
- D. Can explain the output of an Al system
Answer: A
Explanation:
Explanation
One of the main advantages of a machine-based system is its ability to reliably and accurately undertake monotonous and repetitive tasks. This is especially useful for tasks that require a high level of accuracy and precision, such as data entry or analysis. Machine-based systems are also able to process large amounts of data quickly, meaning that they are able to complete tasks more quickly and efficiently than humans. Additionally, machine-based systems can be programmed to take certain decisions and actions based on the input data, allowing them to automate certain processes without the need for human intervention. References:
* BCS Foundation Certificate In Artificial Intelligence Study Guide (2019), AI Systems, Chapter 8.
* https://www.apmg-international.com/en/al-adoption/advantages-of-al/
NEW QUESTION # 39
What function is used in a Neural Network?
- A. Activation.
- B. Trigonometric.
- C. Statistical.
- D. Linear.
Answer: A
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 # 40
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APMG-International Artificial-Intelligence-Foundation Certification Exam is suitable for professionals from various backgrounds, including IT, business, and management. It is especially relevant for those who work in industries that are likely to be impacted by AI, such as healthcare, finance, and retail. Foundation Certification Artificial Intelligence certification is also useful for individuals who wish to stay up-to-date with the latest developments in AI and their potential impact on society.
Latest Artificial-Intelligence-Foundation Pass Guaranteed Exam Dumps Certification Sample Questions: https://pass4sure.examtorrent.com/Artificial-Intelligence-Foundation-prep4sure-dumps.html
