Get Jul-2023 Download Latest & Valid Questions For BCS AIF exam [Q14-Q37]

Get Jul-2023 Download Latest & Valid Questions For BCS AIF exam

Ensure Success With Updated Verified AIF Exam Dumps

BCS AIF certification exam is a valuable credential for anyone looking to enter the field of artificial intelligence. It demonstrates to potential employers that the candidate has a strong foundation in AI and is capable of applying AI techniques to real-world problems. The AIF certification is also a useful way for professionals already working in the AI industry to demonstrate their expertise and advance their careers.

 

NEW QUESTION # 14
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)

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

Answer: C

NEW QUESTION # 15
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference. (Select the missing word.)

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

Answer: C

NEW QUESTION # 16
Ensemble learning methods do what with the hypothesis space?

• A. Select a combination of hypothesis to combine their predictions
• B. Test multiple hypotheses simultaneously.
• C. Extract ergodic solutions.
• D. Use stochastic gradient descent to optimise a network.

Answer: A

Explanation:
https://link.springer.com/referenceworkentry/10.1007/978-0-387-73003-5_293#:~:text=Definition,and%20combine%20them%20to%20use.

NEW QUESTION # 17
Tensor flow is a typical open source what?

• A. Machine learning library.
• B. Agent based modelling application
• C. Cloud based AI application.
• D. Intelligent robot paradigm.

Answer: A

Explanation:
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
https://www.tensorflow.org/#:~:text=TensorFlow%20is%20an%20end%2Dto,and%20deploy%20ML%20powered%20applications.

NEW QUESTION # 18
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 # 19
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 onedimension.

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 # 20
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. Undertakes monotonous tasks reliably and accurately.
• D. Can explain the output of an Al system

Answer: C

NEW QUESTION # 21
What does TRL stand for?

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

Answer: C

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-,Technology%20Readiness%20Level%20(TRL),program%20during%20the%20acquisition%20process.

NEW QUESTION # 22
Reflex and Model-based Reflex are two types of what?

• A. Artificial intelligent agents.
• B. Robot
• C. Compilers.
• D. Algorithms.

Answer: A

NEW QUESTION # 23
What function is used in a Neural Network?

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

Answer: B

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 # 24
The Scrum Master is part of which team?

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

Answer: D

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 # 25
What is one of the MAIN contributions of Al to the rapid development of The Fourth Industrial Revolution?

• A. Automation
• B. Big Data
• C. Al personal assistants.
• D. Enhanced design.

Answer: B

Explanation:
https://research.com/careers/what-is-the-fourth-industrial-revolution

NEW QUESTION # 26
Splitting data into Training and Test data sets is part of what?

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

Answer: A

NEW QUESTION # 27
What is an intelligent robot?

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

Answer: D

NEW QUESTION # 28
How could machine learningmake a robot autonomous?

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

Answer: D

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 # 29
In the 1800's the development of statistics led to___________theorem and is used in probabilistic inference.
(Select the missing word.)

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

Answer: A

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 # 30
Ensemble learning methods do what with the hypothesis space?

• A. Select a combination of hypothesis to combine their predictions
• B. Test multiple hypotheses simultaneously.
• C. Extract ergodic solutions.
• D. Use stochastic gradient descent to optimise a network.

Answer: A

Explanation:
Explanation
https://link.springer.com/referenceworkentry/10.1007/978-0-387-73003-5_293#:~:text=Definition,and%20comb

NEW QUESTION # 31
Ensemble learning methods do what with the hypothesis space?

• A. Test multiple hypotheses simultaneously.
• B. Select a combination of hypothesis to combine theirpredictions
• C. Extract ergodic solutions.
• D. Use stochastic gradient descent to optimise a network.

Answer: B

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 # 32
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:
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/

NEW QUESTION # 33
An agent based model is asimul-ationof autonomous agents (individual and collective). What can be used to
learn from the data generated by thesimul-ations?

• A. A spreadsheet
• B. Paraview.
• C. Python.
• D. Machine Learning.

Answer: A

Explanation:
Explanation
https://www.pnas.org/doi/10.1073/pnas.082080899

NEW QUESTION # 34
Sustainability focuses on which three core areas?

• A. Social, Entrepreneurial and Environmental.
• B. Scientific, Environmental and Economic.
• C. Social, Economic and Entrepreneurial.
• D. Social, Economic and Environmental.

Answer: D

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 # 35
Sustainability focuses on which three core areas?

• A. Social, Entrepreneurial and Environmental.
• B. Scientific, Environmental and Economic.
• C. Social, Economic and Entrepreneurial.
• D. Social, Economic and Environmental.

Answer: D

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

NEW QUESTION # 36
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

NEW QUESTION # 37
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