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BCS Artificial Intelligence Foundation: master AI fundamentals
Contributing to an AI project requires distinguishing real capabilities from hype. Connect data, models and use cases to understand choices and their limitations. Develop reference points for more precise discussions with technical teams and better-supported decisions.
- Duration
- 3 days 21 hours
- Code
- BCSAIFFR Code
- Certification
- EXIN® BCS Artificial Intelligence Foundation Certification
Accredited training for the EXIN® BCS Artificial Intelligence Foundation certification.
Presentation
The integration of artificial intelligence is transforming business models and demands a detailed understanding of how it works. It is no longer just about technology, but about understanding how cognitive systems can sustainably transform your organisation's added value.
During this 3-day course, you will explore how machine learning, neural networks and robotics work in practice. You will learn to identify automation opportunities while managing ethical risks and algorithmic biases inherent in AI projects.
This comprehensive programme equips you to communicate effectively with technical experts and lead innovative projects. It also prepares you for the EXIN BCS Artificial Intelligence Foundation certification exam, an international benchmark validating your digital and strategic understanding (find out more in the Certification tab).
Objectives
By the end of this course, you will be able to:
- define artificial intelligence and its fundamental ethical principles;
- explain the machine learning process and its variants;
- identify artificial neural network applications and how they work;
- understand intelligent agent and problem-solving logic;
- analyse interactions between AI, robotics and the Internet of Things (IoT);
- assess the risks, sustainability and societal impact of autonomous systems;
- prepare for and pass the EXIN BCS Artificial Intelligence Foundation certification exam by mastering all required skills and knowledge.
Program
Module 1: understand AI and its ethical challenges
- Defining AI and distinguishing narrow AI from general AI.
- Analysing ethical risks, transparency and data bias.
- Human-centred, sustainable AI.
Module 2: structure problem-solving
- The role of intelligent agents and their environment.
- Search and planning techniques in expert systems.
- Logic and knowledge representation for decision-making.
Module 3: master machine learning concepts
- Comparing supervised, unsupervised and reinforcement learning.
- The ML project lifecycle: from data collection to training.
- Classical algorithms: linear regression, decision trees and classification.
Module 4: explore neural networks and deep learning
- Artificial neural network architecture (perceptron).
- Advanced applications in computer vision and natural language processing (NLP).
- Key differences between deep learning and traditional machine learning.
Module 5: understand robotics and the future of AI
- Essential robotic system components and sensors.
- Integrating AI into autonomous and mobile robots.
- Future developments and human-machine collaboration.
Module 6: prepare for the EXIN BCS AI Foundation exam
- Review of key points and concepts covered in modules 1–5.
- Mock exam under realistic conditions (40 multiple-choice questions).
- Certification exam tips and guidance (time management, multiple-choice answer strategies).
Audience
This course is intended for professionals seeking a clear, structured understanding of AI, including:
- project managers leading digital transformation to integrate intelligent solutions into processes;
- functional consultants translating business needs into technical specifications for development teams;
- decision-makers and managers assessing cognitive technologies' risks and return on investment to guide strategy;
- IT engineers seeking to expand their skills into data science and algorithms.
Prerequisites
This course has the following prerequisites:
- Professional experience: an interest in digital technology or project management experience is strongly recommended to contextualise theory within a business setting.
- Basic knowledge: general IT awareness and elementary logic or mathematics.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
- Mock exam
Course highlights
- EU AI Act alignment: the programme incorporates European regulation requirements to provide a solid understanding of current legal obligations.
Practical tools: benefit from analysis frameworks and concrete templates to assess and manage AI projects. - Dual accreditation: learning content jointly validated by EXIN and the prestigious British Computer Society (BCS).
Recognised certification: validate your skills with the international EXIN BCS Artificial Intelligence Foundation qualification, demonstrating your understanding of AI terminology and general principles.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
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