BCS Artificial Intelligence Foundation Certificate – Virtual Classroom

How does the Exam Pass Guarantee work?

We have found our Virtual Classroom training has provided higher pass rates, which has made us confident to offer an Exam Pass Guarantee, so you know we’ll support you until you are certified.

With our Exam Pass Guarantee, if you do not pass the exam after attending this training course with us, you will be eligible to attend the same training again for free.

All we ask is that you:

•    Attend all class days and complete all assignments
•    Take the exam within 30 days of completing your Virtual Classroom training
•    Request your course re-enrolment within 30 days of the failed exam attempt

Please Note:

Students retaking the course are required to use the materials and books distributed to them in their original course session. Failure to provide these materials will result in the student being charged for replacement materials.

*Exam Pass Guarantee does not include the resit exam; this would need to be purchased at an additional cost.

Is the BCS Artificial Intelligence Foundation course suitable for me?  

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

What jobs can I apply for after my BCS Artificial Intelligence training? 

Artificial Intelligence training would enable you to work towards an entry-level  career as an: 

•    Machine Learning Researcher - £35k
•    Data Mining and Analysis Professional - £47k
•    Data Scientist - £47k
•    Business Intelligence (BI) Developer - £47k 
•    Machine Learning Engineer - £52k
•    Artificial Intelligence Engineer - £65k

(Source: JobsInIT)

Artificial Intelligence training would also help enhance other sectors, including:   

•    Science 
•    Engineering
•    Web Page Development 
•    Professional Research
•    Organisational Change
•    Process Management 
•    Business Change Managers 
•    Program Management

BCS Artificial Intelligence 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. 

BCS Artificial Intelligence Syllabus

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.

BCS Artificial Intelligence Exam Details 

Exam Details

Type - Multiple-choice.

Number of questions – 40.

Duration - 60-mins.

Supervised - Yes.

Open Book - No.

Pass Mark – 26/40 (65%).