APMG-International Artificial-Intelligence-Foundation Exam Questions: Attain Your Professional Career Targets [2023]

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The exam is designed to test the candidate's understanding of the underlying principles of AI, as well as their ability to apply these principles to real-world scenarios. The certification is intended for individuals who have a basic understanding of computer science and programming, but who may not have any prior experience in AI. The exam is designed to be accessible to individuals from a wide range of backgrounds and industries, including software development, data science, and business analysis.

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APMG-International Foundation Certification Artificial Intelligence Sample Questions (Q10-Q15):

NEW QUESTION # 10
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?

A. Boosting.
B. Over-fitting
C. Iteration.
D. Activation.

Answer: A

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 # 11
From the Ell's ethics guidelines for Al, what does 'The Principle of Autonomy,' mean?

A. Al systems will preserve human agency.
B. Robots will have freewill.
C. Al agents will behave as humans.
D. Al systems will be human-centric

Answer: A

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 # 12
What is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a class of problems?

A. A paradigm.
B. An approach.
C. An algorithm.
D. A set

Answer: A

Explanation:
Explanation
A paradigm is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a class of problems. Paradigms are often used in Artificial Intelligence to provide a structure for problem solving, allowing for better understanding of the problem and providing a framework for developing a solution. For example, the logic-based approach is a paradigm that uses logical reasoning to solve problems.
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 # 13
Human-centric trustworthy Al must be...

A. tested by humans.
B. quality assurance certified.
C. continually assessed and monitored.
D. financially sustainable.

Answer: C

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 # 14
The EU and United Nations have made designing for all individuals a core principle. What is this type of design called?

A. Utopic design.
B. Core design
C. Biophilic design.
D. Universal design.

Answer: D

Explanation:
Explanation
https://universaldesign.ie/What-is-Universal-Design/
Universal design is a type of design that takes into account the needs of all individuals, regardless of age, ability, or physical condition. It is a principle that is embraced by the European Union and the United Nations, and it is based on the idea that products, services, and environments should be designed to be usable by the widest range of people possible. Universal design emphasizes accessibility, usability, and inclusivity, and it is often used to create products and services that are easy to use for people of all ages and abilities.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www

NEW QUESTION # 15
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