Foundation Certificate in Artificial Intelligence (FCAI)

Learn the general principles of AI, its potential implications and capabilities and how to assess AI products and services from multiple angles. The training program provides insightful information about flooring technology, compartmentation industry, special inspection agency members, education sessions. The training program is suitable for employees like FCIA contractor who want to gain experience in skills including firestop systems and work for the special inspection agencies. The firestop contractors international association needs a workforce with skills for fire protection. Hence, the floor covering institute offers the best training course for the flooring industry. The exams encourage people to make a good career in international firestop council and similar workforce industry. The FCIA newsletter is helpful for the members of the floor covering institute who want to take the training program.

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Course Style

Live Instructor led. Face-to-face or attend from anywhere.

Skill up and get certified, guaranteed

Exam Pass Guarantee

Exam Pass Guarantee

If you don’t pass your exam on the first attempt for flooring experience, You get to re-sit the training course programs for free.

100% Satisfaction Guarantee

100% Satisfaction Guarantee

If you’re not 100% satisfied with your training at the end of the first day, you may withdraw and enroll in a different Classroom course.

Knowledge Transfer Guarantee

Knowledge Transfer Guarantee

High Impact Learning Solutions Designed for students to acquire skills and obtain certification,.

What is included?

  • 3 days of training.
  • Course material/Slides.
  • Examination Fees.
  • 95.8% Certification Success in First Attempt.
  • Classroom training or attend from anywhere.
  • Training delivered by Professionals with enormous industry experience. 
  • Total comprehensive exam preparation.

What you will Learn?

  • Ethical and sustainable human and artificial intelligence.
  • Artificial Intelligence and robotics.
  • Applying the benefits of AI – challenges and risks.
  • Starting AI: how to build a Machine Learning toolbox – theory and practice.
  • The management, role and responsibilities of humans and machines.

Award-winning training that you can trust

Who should attend?

Engineers, scientists, organisational change practitioners, service architects, program and planning managers, web developers, chief technical officers, service provider portfolio strategists/leads, business strategists and consultants wishing to achieve an AI qualification. The training is suitable for people who want to try their hands on apprenticeships in fire resistance and want expertise in firestop products. This is helpful for suppliers, employer, buildings, and manufacturers.

Anyone with an interest in (or needs to implement) artificial intelligence in an organisation, especially those working in areas such as science, engineering, flooring, engineering, finance, education or IT services.

Course Dates

29 – 30 Mar, 2021

20 – 22 Sept, 2021

Course Outline

Ethical and Sustainable Human and Artificial Intelligence (20%)

Candidates will be able to:

Candidates will be able to:

1.1. Recall the general definition of Human and Artificial Intelligence (AI).

1.1.1. Describe the concept of intelligent agents.

1.1.2. Describe a modern approach to Human logical levels of thinking using

Robert Dilt’s Model.

1.2. Describe what are Ethics and Trustworthy AI, in particular:

1.1.1. Recall the general definition of Ethics.

1.2.1. Recall that a Human Centric Ethical Purpose respects fundamental rights,

principles and values.

1.2.2. Recall that Ethical Purpose AI is delivered using Trustworthy AI that is

technically robust.

1.2.3. Recall that the Human Centric Ethical Purpose Trustworthy AI is

continually assessed and monitored.

1.3. Describe the three fundamental areas of sustainability and the United Nation’s

seventeen sustainability goals.

1.4. Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial

Revolution’.

1.5. Understand that ML is a significant contribution to the growth of Artificial

Intelligence.

1.5.1. Describe ‘learning from experience’ and how it relates to Machine Learning

(ML) (Tom Mitchell’s explicit definition).

2 Artificial Intelligence and Robotics (20%)

2.1. Demonstrate understanding of the AI intelligent agent description, and:

2.1.1. list the four rational agent dependencies.

2.1.2. describe agents in terms of a performance measure, environment, actuators

and sensors.

2.1.3. describe four types of agent: reflex, model-based reflex, goal-based and

utility-based.

2.1.4. identify the relationship between AI agents with Machine Learning (ML).

2.2. Describe what a robot is and:

2.2.1. Describe robotic paradigms,

2.3. Describe what an intelligent robot is and:

2.3.1. Relate intelligent robotics to intelligent agents.

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BCS Foundation Certificate in Artificial Intelligence

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  1. 3 Applying the benefits of AI – challenges and risks (15%)

    3.1. Describe how sustainability relates to human-centric ethical AI and how our values

    will drive our use of AI will change humans, society and organisations.

    3.2. Explain the benefits of Artificial Intelligence by.

    3.2.1. list advantages of machine and human and machine systems.

    3.3. Describe the challenges of Artificial Intelligence, and give;

    3.3.1. general ethical challenges AI raises.

    3.3.2. general examples of the limitations of AI systems compared to human

    systems.

    3.4. Demonstrate understanding of the risks of AI project, and:

    3.4.1. give at least one a general example of the risks of AI,

    3.4.2. describe a typical AI project team in particular,

    3.4.2.1. describe a domain expert,

    3.4.2.2. describe what is ‘fit-of-purpose’,

    3.4.2.3. describe the difference between waterfall and agile projects.

    3.5. List opportunities for AI.

    3.6. Identify a typical funding source for AI projects and relate to the NASA Technology

    Readiness Levels (TRLs).

    4 Starting AI how to build a Machine Learning Toolbox – Theory and Practice (30%)

    4.1. Describe how we learn from data – functionality, software and hardware,

    4.1.1. List common open source machine learning functionality, software and

    hardware.

    4.1.2. Describe the introductory theory of Machine Learning.

    4.1.3. Describe typical tasks in the preparation of data.

    4.1.4. Describe typical types of Machine Learning Algorithms.

    4.1.5. Describe the typical methods of visualising data.

    4.2. Recall which typical, narrow AI capability is useful in ML and AI agents’

    functionality.

    5 The Management, Roles and Responsibilities of humans and machines (15%)

    5.1. Demonstrate an understanding that Artificial Intelligence (in particular, Machine

    Learning) will drive humans and machines to work together.

    5.2. List future directions of humans and machines working together.

    5.3. Describe a ‘learning from experience’ Agile approach to projects

    5.3.1. Describe the type of team members needed for an Agile project career.

Prerequisites

None, but the Essentials Certificate in Artificial Intelligence (ECIA) is the recommended.

Are you ready to get started?