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BCS AIF Exam Syllabus Topics:

Topic 1
  • Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality
  • The Management, Roles and Responsibilities of humans and machines
Topic 2
  • Describe a ‘learning from experience’ Agile approach to projects
  • Describe the type of team members needed for an Agile project
Topic 3
  • Demonstrate understanding of the AI intelligent agent description
  • Starting AI how to build a Machine Learning Toolbox - Theory and Practice
Topic 4
  • Recall that the Human Centric Ethical Purpose Trustworthy AI is continually assessed and monitored
  • Describe the difference between waterfall and agile projects
Topic 5
  • Describe the three fundamental areas of sustainability and the United Nation’s seventeen sustainability goals
  • General examples of the limitations of AI systems compared to human systems
Topic 6
  • List future directions of humans and machines working together
  • Describe what are Ethics and Trustworthy AI, in particular
Topic 7
  • List common open source machine learning functionality, software and hardware
  • Relate intelligent robotics to intelligent agents
Topic 8
  • Describe four types of agent: reflex, model-based reflex, goal-based and utility-based
  • Explain the benefits of Artificial Intelligence
Topic 9
  • Describe agents in terms of performance measure, environment, actuators and sensors
  • Recall the general definition of Human and Artificial Intelligence (AI)
Topic 10
  • Recall that Ethical Purpose AI is delivered using Trustworthy AI that is technically robust
  • Recall the general definition of Ethics
Topic 11
  • Understand that ML is a significant contribution to the growth of Artificial Intelligence
  • Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution
Topic 12
  • Describe how we learn from data – functionality, software and hardware
  • Identify the relationship of AI agents with Machine Learning (ML)

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BCS Foundation Certificate In Artificial Intelligence Sample Questions (Q34-Q39):


The EU's Ethical Guidelines use what to demonstrate trustworthy Al?

  • A. Customer feedback.
  • B. A human-centric value system.
  • C. UN's sustainability goals.
  • D. A quality assurance plan.

Answer: C


What function is used in a Neural Network?

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

Answer: D



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. 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,


What are monotonous and repetitive tasks, that require accuracy BEST suited to?

  • A. Artificial General Intelligence.
  • B. Human.
  • C. Machine.
  • D. Human plus machine.

Answer: A


What is defined as a machine that can carry out a complex series of tasks automatically?

  • A. A production line.
  • B. A robot
  • C. An autonomous vehicle.
  • D. A computer.

Answer: B




Narrow or weak Al can be useful to robots.

Which of the following is an example of narrow Al?

  • A. Artificial General Al.
  • B. Conscious integration.
  • C. NLP - Natural Language Processing.
  • D. Conscioussimul-ation.

Answer: C



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