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BCS AIF Exam Syllabus Topics:TopicDetailsTopic 1Describe how we learn from data – functionality, software and hardware Identify the relationship of AI agents with Machine Learning (ML)Topic 2Demonstrate understanding of the AI intelligent agent description Starting AI how to build a Machine Learning Toolbox - Theory and PracticeTopic 3Understand that ML is a significant contribution to the growth of Artificial Intelligence Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial RevolutionTopic 4Demonstrate understanding of the risks of AI project Ethical and Sustainable Human and Artificial IntelligenceTopic 5Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality The Management, Roles and Responsibilities of humans and machinesTopic 6Identify a typical funding source for AI projects and relate to the NASA Technology Readiness Levels (TRLs) Describe a modern approach to Human logical levels of thinking using Robert Dilt’s ModelTopic 7Recall that Ethical Purpose AI is delivered using Trustworthy AI that is technically robust Recall the general definition of EthicsTopic 8Describe four types of agent: reflex, model-based reflex, goal-based and utility-based Explain the benefits of Artificial IntelligenceTopic 9List common open source machine learning functionality, software and hardware Relate intelligent robotics to intelligent agentsTopic 10List future directions of humans and machines working together Describe what are Ethics and Trustworthy AI, in particularBCS Foundation Certificate In Artificial Intelligence Sample Questions (Q31-Q36):
NEW QUESTION # 31
A human manipulates what using their intelligence?
Answer: B
NEW QUESTION # 32
Ensemble learning methods do what with the hypothesis space?
Answer: A
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 # 33
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
Answer: A
Explanation:
NEW QUESTION # 34
Which of the following is an advantage of a machine based system?
Answer: A
NEW QUESTION # 35
An Al agentrelies on its perceptual input.This is called the agent's what?
Answer: A
Explanation:
Explanation
* Performance Measure of Agent It is the criteria, which determines how successful an agent is.
* Behavior of Agent It is the action that agent performs after any given sequence of percepts.
* Percept It is agent's perceptual inputs at a given instance.
* Percept Sequence It is the history of all that an agent has perceived till date.
* Agent Function It is a map from the precept sequence to an action.
Agent Terminology
https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_agents_and_environments.htm
NEW QUESTION # 36
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