Course Features

Pre-course reading

4-hour online sessions

Live, interactive Instructor-led training

Unlimited 1-2-1 coaching

Exam preparation

60-minute online BCS exam

BCS Accredited Training Partner

Course Overview

Launched in 2019, the BCS Foundation Certificate in Artificial Intelligence was refreshed and reformatted in August 2024 to provide a comprehensive introduction to this innovative and rapidly growing field. As the adoption of AI increases across all sectors of the economy, so does the need for certified professionals who can address the ethical challenges that AI raises. It's not enough to create AI systems that can perform tasks efficiently; we must also ensure that they are developed in a way that's fair, safe, and beneficial to everyone.

The BCS AI Foundation extends beyond the scope and detail of the related BCS Essentials Certificate in AI to address the fundamental principles and concepts of AI, along with its practical implications in the real world. Participants will learn the history of AI from its origins to its modern re-emergence, with a particular emphasis on machine learning, neural networks, robotics, generative AI and large language models (LLMs).

The BCS AI Foundation considers the various opportunities in which AI tools and applications can transform business services as we move towards a more technologically advanced society. Attendees will learn about performing financial cost-benefit analysis, conducting impact assessments, and how to structure a business case to justify the undertaking of an AI project and secure funding.

With the aim of prioritising ethical and sustainable AI solutions, the BCS AI Foundation examines the challenges and risks associated with AI projects, such as those related to privacy, transparency and potential biases in algorithms that could lead to unintended consequences. In addressing these challenges, the course reviews the pre-existing regulatory landscape, including the UK General Data Protection Regulation (GDPR) and the Data Protection Act 2018 (DPA), along with AI-related laws such as the EU Artificial Intelligence Act (AI Act). Participants will also explore the role of data, effective risk management strategies, compliance, and ongoing governance of the AI lifecycle.

The BCS AI Foundation is delivered online by attending four consecutive 4-hour live online sessions. The course follows the latest BCS Syllabus (v2.0) and prepares participants for the 60-minute multiple-choice BCS Foundation Exam, administered separately via Questionmark through online remote proctoring.

Course Costs

Get this BCS Foundation Certificate in Artificial Intelligence v2.0 for:

£1,295.00 + VAT

10% discount for subscribing to our PrivacyNewsfeed & Training Announcement Newsletters
15% additional online saving for multiple bookings on public schedule courses
In-company options available for teams of 6 or more

BCS training package includes:

4 x 4-hour live online sessions on consecutive days
Entrance to the 60-minute, multiple-choice online BCS Examination
1-2-1 coaching and support
1st year BCS Associate membership

Course materials:

Detailed eBook course manual (see here for eBook features & print options)
Includes free lifetime updates, which means it will never go out of date
Full course PowerPoint presentation
Exercises & revision materials
Sample exam questions

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Intended Audience

The BCS Foundation Certificate in Artificial Intelligence is suitable for a range of non-technical business roles, including middle and senior management professionals working with teams expected to create or use AI tools and applications:

AI governance teams
AI ethics board members
Data Protection Officers (DPOs) & practitioners
Governance, risk & compliance professionals
Legal professionals advising on information law
Privacy engineers
Data scientists, analysts, & architects
Systems administrators, developers, & engineers
Information security, IT security, & IT managers
Software engineers, programmers
Test managers & QA engineers
IT & infosec auditors
Ethical hackers & forensics investigators
Website & game developers, UX/UI designers

Learning Outcomes

Attendees on the BCS Foundation Certificate in Artificial Intelligence will:

Understand the key terminology and general principles of AI
Explore the history of AI from its origins in the 1950s to the re-emergence of big data, machine learning and the development of neural networks, deep learning and large language models, which have led to generative and agentic AI
Discover strategies for addressing ethical challenges in AI projects
Understand the legal considerations when using or developing AI tools and applications, including the UK GDPR, DPA18 and the EU AI Act
Consider how AI technologies can be used to support business activities
Discover how to identify opportunities for AI use
Develop and structure a business case to secure funding for an AI project
Learn how to mitigate AI risks and maintain control over financial costs when implementing AI projects
Consider ongoing AI governance activities related to compliance and risk management throughout the AI lifecycle
Recognise the importance of implementing an employee-wide AI skills development and literacy programme
Consider the impact of AI on the future of society and business

Why experienced data protection practitioners should attend this course?

While it used to be sufficient for data protection professionals to possess an expert-level understanding of relevant legal and regulatory frameworks, modern practitioners are increasingly being asked to advise on non-legal aspects of utilising and protecting personal data. To stay current, practitioners must build on their existing knowledge of data protection laws to include a detailed understanding of AI. This is particularly relevant when considering automated decision-making and ethical issues such as algorithmic bias, fairness, and transparency.

Data protection practitioners will find the BCS Foundation Certificate in Artificial Intelligence an ideal entry point into the field of AI governance. However, to continue their professional development, they will likely need to advance to more in-depth programmes over time.

For new, less-experienced team members, the BCS Essentials Certificate in AI offers a lighter introduction to the subject.

Why is a responsible approach to AI development so important?

As the rapid adoption of artificial intelligence (AI) technologies continues to spread across every industry sector, from law enforcement to healthcare and manufacturing to professional services, the need for trustworthy and effective implementation has never been greater. Organisations are no longer asking if they should adopt AI but how they can do so ethically, reliably, and at scale.

While the potential for AI to transform public service delivery and enhance corporate competitiveness through business efficiencies, productivity gains, and innovation is significant, the challenges involved in successfully implementing AI technologies are substantial. Recent research indicates that the failure rate of AI projects can be as high as 80%, twice that of traditional IT programs.

In order to effectively oversee the implementation of AI projects, organisations must take a comprehensive approach to responsible AI development. Without thorough and systematic oversight, there is a considerable risk that AI projects may not deliver against their stated objectives, which could result in unintended consequences and escalating costs, jeopardising the AI project's operational and financial viability. The only solution, therefore, is to ensure robust AI governance must not be overlooked.

Course Itinerary:

Module 1: An introduction to AI and its historical development

An introduction to key AI definitions and terms
The development of AI from the 1956 Dartmouth conference to Big Data, the Internet of Things and Large Language Models (LLMs)
The difference between task-specific (narrow) and general (strong) AI:
- Narrow AI examples include spam filtering, image and speech recognition, language translation, and virtual assistants
- Strong AI aims to replicate human intelligence, and has the capacity to understand or learn any intellectual task
Consider the ethical, social, economic and environmental impact of AI on society
Sustainability measures to help reduce the environmental impact of AI

Module 2: Ethical and legal considerations

The role of ethics in AI:
- What is ethics?
- Differences between ethics and law
Key ethical concerns in AI:
- Potential for bias, unfairness and discrimination
- Data privacy and protection
- Impact on employment and the economy
Guiding principles behind the ethical development and use of AI, including:
- UK AI principles of safety, security and robustness, transparency and explainability, fairness, accountability and governance, and contestability and redress
Strategies for addressing ethical challenges in AI projects
The need and role of regulation in AI
- AI regulation landscape
- UK GDPR and DPA18
- International Standards
The process of risk management in AI:
- How to identify AI risks
- Risk management techniques
- Risk mitigation strategies
- Importance of minimising risk in relation to AI adoption

Module 3: Enablers of AI

Common examples of where AI tools and applications are used in everyday life
The role of robotics
The field of machine learning (ML):
- Neural networks
- Deep learning
- Large language models (LLMs)
Common ML concepts
Supervised and unsupervised learning

Module 4: Finding and using data for AI purposes

Data definitions and terms
5 characteristics of data quality
Data-driven insights and decision-making
Implications of poor quality data
Risks associated with handling data in AI
The scientific method of learning from experience
The purpose and use of big data
Data visualisation techniques and tools
Generative AI
How data is used to train AI in the ML process

Module 5: How organisations use AI

Identifying opportunities to use AI for:
- Automation
- Repetative tasks
- Content creations
How to develop and structure an AI business case
How to identify and categorise stakeholders for relevent AI projects
How to identify the risks, costs and benefits when implementing an AI project or solution
- Risk analysis
- Risk appetite
- Risk management strategies
- Cost-benefit analysis
- Financial costs and forcasting
Different project management approaches
Ongoing AI governance activities:
- Compliance
- Risk management
- AI Lifecycle

Module 6: Future planning and impact

AI roles and career paths
AI literacy and skills development
Real-world AI applications
Consciousness and its impact on ethical AI
- Human consciousness
- AI consciousness
- AI projects in light of ethical considerations and consciousness
- Ethical challenges associated with artificial consciousness

BCS AI Foundation Syllabus:

Foundation Certificate in Artificial Intelligence (AI-F)

Syllabus version 2.0
August 2024

Download the new syllabus (PDF)

BCS AI Foundation Examination:

Duration and Format of the Examination

The BCS Foundation Certificate in Artificial Intelligence exam format is a 1-hour multiple-choice examination. The exam is closed book, i.e. no materials can be taken into the examination room.

Exam Format

Type	40 Multiple choice questions
Duration	60 Minutes
Supervised	Yes
Open Book	No
Pass Mark	26/40 \| 65%
Calculators	No calculators nor mobile technology is permitted
Delivery	Online

Additional time for candidates requiring Reasonable Adjustments

Adjustments and/or additional time can be requested in line with the BCS reasonable adjustments policy for candidates with a disability or other special considerations, including English as a second language.