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One of the main benefits of the APMG-International Artificial Intelligence Foundation certification is that it helps organizations identify the best practices to implement AI. The certification is also an excellent opportunity for individuals to learn how to leverage AI to solve business problems and create new business opportunities.
The exam is designed for professionals who want to establish a solid foundation in AI and understand how it can be used to solve complex business problems. The certification covers various topics, including machine learning, natural language processing, computer vision, and robotics. The exam format includes multiple-choice questions, and candidates are required to achieve a passing score to obtain the certification. The APMG-International Artificial-Intelligence-Foundation (Foundation Certification Artificial Intelligence) Certification Exam is ideal for data scientists, software developers, business analysts, and anyone who is interested in learning about AI and its applications.
NEW QUESTION # 24
What function is used in a Neural Network?
- A. Statistical.
- B. Trigonometric.
- C. Activation.
- D. Linear.
Answer: C
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 # 25
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. Paraview.
- B. A spreadsheet
- C. Machine Learning.
- D. Python.
Answer: C
Explanation:
Explanation
An agent based model is a simulation of autonomous agents (individual and collective). Machine learning can be used to learn from the data generated by the simulations. Machine learning algorithms can analyze the data generated by simulations and identify patterns, which can then be used to help the agent make decisions and take actions. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Simulation and Modelling", p.101-104.
[2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"
NEW QUESTION # 26
Sustainability focuses on which three core areas?
- A. Social, Economic and Environmental.
- B. Social, Entrepreneurial and Environmental.
- C. Scientific, Environmental and Economic.
- D. Social, Economic and Entrepreneurial.
Answer: A
Explanation:
Explanation
The term sustainability is broadly used to indicate programs, initiatives and actions aimed at the preservation of a particular resource. However, it actually refers to four distinct areas: human, social, economic and environmental - known as the four pillars of sustainability.
https://www.futurelearn.com/info/courses/sustainable-business/0/steps/78337#:~:text=However%2C%20it%20ac Sustainability focuses on these three core areas because they all have an impact on the environment and society. Social sustainability is concerned with the relationships between people and how to create a society that is equitable and fair for all members. Economic sustainability focuses on the creation of a viable economic system that provides for the needs of the present without compromising the ability of future generations to meet their own needs. Environmental sustainability focuses on protecting natural resources, ecosystems and habitats, and minimizing the impact of human activities on the environment.
References: https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/ https://www
NEW QUESTION # 27
A human manipulates what using their intelligence?
- A. Objective
- B. Environment
- C. Mission
- D. Space
Answer: B
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 # 28
Ensemble learning methods do what with the hypothesis space?
- A. Extract ergodic solutions.
- B. Use stochastic gradient descent to optimise a network.
- C. Test multiple hypotheses simultaneously.
- 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 # 29
Reflex and Model-based Reflex are two types of what?
- A. Algorithms.
- B. Artificial intelligent agents.
- C. Robot
- D. Compilers.
Answer: B
Explanation:
Explanation
Reflex and Model-based Reflex are two types of Artificial Intelligent Agents. Artificial Intelligent Agents are computer systems designed to act and think in a manner similar to humans,incorporating elements of problem solving, decision-making, communication, and learning. Reflex agents are reactive agents which act based on the current environment and conditions, while Model-based Reflex agents use a model of the environment to make decisions. 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 # 30
Splitting data into Training and Test data sets is part of what?
- A. Machine learning post processing.
- B. Machine learning data preparation.
- C. Batch learning.
- D. High performance computing strategy.
Answer: B
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 # 31
Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?
- A. Autonomous vehicles.
- B. Autonomous wheelchairs.
- C. Diagnostic image analysis
- D. Automated blood sampling.
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 # 32
What is defined as a machine that can carry out a complex series of tasks automatically?
- A. A computer.
- B. An autonomous vehicle.
- C. A robot
- D. A production line.
Answer: A
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 # 33
With a large dataset, limited computational resources or frequent new data to learn from, we can adopt what type of machine learning?
- A. Patchwork learning.
- B. Big Data learning.
- C. Batch learning.
- D. Online learning.
Answer: D
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 # 34
What is defined as a philosophy, or set of assumptions and/or techniques, which characterise an approach to a class of problems?
- A. A set
- B. A paradigm.
- C. An algorithm.
- D. An approach.
Answer: B
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 # 35
A vector in vector calculus is a quantity that has magnitude and direction.
What is a vector in computer programming?
- A. An array of complex numbers
- B. A constant
- C. A two-dimensional array of scalars.
- D. An array with one dimension.
Answer: D
Explanation:
Explanation
In computer programming, a vector is a data structure that contains a collection of elements that are all of the same type. Each element in the vector has an associated index, which can be used to access and modify the element at that index. Vectors are commonly used to store collections of numerical values (e.g., integers or floating-point numbers) or strings, but they can also be used to store any type of data.
References: [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, Page number 36 [2] APMG International, "What is a Vector in Computer Programming?", https://apmg-international.com/en/blog/what-is-a-vector-in-computer-programming/ [3] EXIN, "What is a Vector in Computer Programming?", https://www.exin.com/blog/what-is-a-vector-in-computer-programming/
NEW QUESTION # 36
What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?
- A. Activation.
- B. Iteration.
- C. Over-fitting
- 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 # 37
An Al agent relies on its perceptual input. This is called the agent's what?
- A. Position
- B. World
- C. Percept
- D. Environment
Answer: C
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 An AI agent relies on its perceptual input, which is referred to as the agent's percept. This is the data that the agent collects through its sensors about its environment. The percept allows the agent to make decisions and take actions based on its environment. The agent's percept is important for Artificial Intelligence systems to be able to operate effectively. References:
[1] BCS Foundation Certificate In Artificial Intelligence Study Guide, "Reinforcement Learning", p.96-97. [2] APMG-International.com, "Foundations of Artificial Intelligence" [3] EXIN.com, "Foundations of Artificial Intelligence"
NEW QUESTION # 38
What are monotonous and repetitive tasks, that require accuracy BEST suited to?
- A. Machine.
- B. Artificial General Intelligence.
- C. Human.
- D. Human plus machine.
Answer: A
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 # 39
Which of the following is an advantage of a machine based system?
- A. Capable of sympathising with humans.
- B. Able to judge ambiguous and unknown situations.
- C. Can explain the output of an Al system
- D. Undertakes monotonous tasks reliably and accurately.
Answer: D
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 # 40
......
The APMG-International Artificial-Intelligence-Foundation Exam is a vendor-neutral certification that is recognized globally. It is an online exam that consists of 40 multiple-choice questions, and candidates are given 60 minutes to complete it. The exam covers topics such as the history of AI, the different types of AI, and the ethical considerations surrounding AI. The certification is suitable for a wide range of professionals, including developers, data scientists, and business analysts. It is an excellent way to demonstrate to employers and clients that you have a strong understanding of AI and its potential applications.
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