BCS Artificial Intelligence Foundation Certificate – Virtual Classroom

The BCS Foundation course in Artificial Intelligence is part of our new line up for Artificial Intelligence training. This course builds upon the knowledge gained from the Essential Artificial Intelligence training course.

This course in Artificial Intelligence incorporates and builds on the essentials certification to develop a portfolio of AI examples using the basic process of machine learning. It shows how AI delivers business, engineering, and knowledge benefits.

If you are interested in gaining key essential AI knowledge, we recommend you first enrol onto our BCS Essentials Certificate in Artificial Intelligence training course.

Key features
  • Delivery Method: Virtual Classroom
  • Exam: Included
  • Duration: 3 Days
  • Certified & Experienced Trainers
  • Join a community of over 575,000 learners
  • Interest-Free Payments

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Key features
  • Delivery Method: Virtual Classroom
  • Exam: Included
  • Duration: 3 Days
  • Certified & Experienced Trainers
  • Join a community of over 575,000 learners
  • Interest-Free Payments
Course Details

What is the BCS Foundation Certificate in Artificial Intelligence course?

Use this Artificial Intelligence training course to take your knowledge and understanding of AI further, and discover the capabilities and potential implications of AI.

AI is a methodology used to imitate human intelligence behaviour and learn from experience. Through this AI training course, you will gain a knowledge and understanding of the terminology and principles of AI.

This syllabus covers:

  •    Potential benefits and challenges of Ethical and Sustainable Robust Artificial Intelligence
  •    Basic process of Machine Learning (ML) – Building a Machine Learning Toolkit
  •    Challenges and risks associated with an AI project
  •    Future of AI and Humans in work.

The Foundation Certificate includes and expands on the knowledge taught in the BCS Essentials Certificate in AI. Upon completion of this training course and exam, you’ll gain a BCS Foundation certificate in Artificial Intelligence.

Who is this course suitable for?  

The Artificial Intelligence Foundation certificate is aimed at individuals who have an interest in, or need to implement, AI in their organisation.

Middle and Senior Managers, who run or organise teams to create AI dependent services and applications, would also benefit from the principles taught throughout this training.

Typically, this course will benefit individuals who work in the following sectors:

  •    Science
  •    Engineering
  •    Knowledge Engineering
  •    Finance
  •    IT Services

Career Opportunities

While this training would be useful for many different backgrounds and job titles, this Artificial Intelligence training course would benefit: 

  •    Scientists - £30k
  •    Engineers - £33k
  •    Web Page Developers - £35k
  •    Professional Research Managers - £39k
  •    Organizational Change Managers - £45K
  •    Process Managers - £49k
  •    Business Change Managers - £51k
  •    Program Managers - £62k
  •    Chief Information Officers - £136K
  •    Chief Technical Officers - £148k

(Source: Glassdoor)

Why choose e-Careers to study this course

With over 10 years’ experience in the training and education sector, we have enhanced and fine-tuned our overall training offering; from selecting the best trainers, having the most relevant course materials and best customer support. We have trained over 575,000 delegates from around the world and have achieved a 5-star rating, from over 8,500 students on Trustpilot.

You’ll also benefit from:

  •    Highly quality training
  •    Expert Tutor Support
  •    Interest-Free Payment Plans

Course Details & Syllabus

Learning Outcomes

  •    Human-centric Ethical and Sustainable Human and Artificial Intelligence.
  •    Artificial Intelligence and Robotics.
  •    Applying the benefits of AI projects - challenges and risks.
  •    Machine Learning Theory and Practice – Building a Machine Learning Toolbox.
  •    The Management, Roles and Responsibilities of Humans and Machines – The Future of AI. 


Ethical and Sustainable Human and Artificial Intelligence (20%)

  •    Recall the general definition of Human and Artificial Intelligence (AI).
  •    Describe the concept of intelligent agents.
  •    Describe a modern approach to Human logical levels of thinking using Robert Dilt’s Model.
  •    Describe what are Ethics and Trustworthy AI.
  •    Describe the three fundamental areas of sustainability and the United Nation’s seventeen sustainability goals.
  •    Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.
  •    Understand that ML is a significant contribution to the growth of Artificial Intelligence.
  •    Describe ‘learning from experience’ and how it relates to Machine Learning (ML) (Tom Mitchell’s explicit definition).

Artificial Intelligence and Robotics (20%)

  •    Demonstrate understanding of the AI intelligent agent description
  •    Describe what a robot is, robotic paradigms and describe what an intelligent robot is

Applying the benefits of AI - challenges and risks (15%)

  •    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.
  •    Explain the benefits of Artificial Intelligence.
  •    Describe the challenges of Artificial Intelligence.
  •    Demonstrate understanding of the risks of AI project.
  •    List opportunities for AI.
  •    Identify a typical funding source for AI projects and relate to the NASA Technology Readiness Levels (TRLs).
  •    Starting AI how to build a Machine Learning Toolbox - Theory and Practice (30%)
  •    Describe how we learn from data – functionality, software, and hardware,
  •    List common open source machine learning functionality, software, and hardware.
  •    Describe introductory theory of Machine Learning.
  •    Describe typical tasks in the preparation of data.
  •    Describe typical types of Machine Learning Algorithms.
  •    Describe the typical methods of visualising data.
  •    Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality.

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

  • Demonstrate an understanding that Artificial Intelligence (in particular, Machine Learning) will drive humans and machines to work together.
  • List future directions of humans and machines working together.
  • Describe a ‘learning from experience’ Agile approach to projects
  • Describe the type of team members needed for an Agile project.

Exam Details

Type - Multiple choice

Number of questions – 40

Duration - 60 Minutes

Supervised - Yes

Open Book - No

Pass Mark – 26/40 (65%)

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