The Introduction to AI course provides a foundational understanding of Artificial Intelligence — from its history and core principles to real-world use cases. You’ll explore how AI systems learn, make predictions, and support human decision-making. Designed for learners of all backgrounds, this course helps you build a solid base for more advanced AI studies and understand the role of AI in shaping the future of technology and society.

The Accredited AI Agenda AI Lesson introduces learners to the strategic vision behind responsible and effective AI adoption. This course explores how AI technologies are transforming business, governance, and society — with a focus on innovation, transparency, and ethical implementation. Learners will gain insight into emerging AI trends, policy frameworks, and real-world examples of how AI can create measurable impact when guided by the right principles.

This intensive programme prepares participants for FractAI's EPAI professional accreditation. Through structured teaching, mentoring, and guided application support, learners gain a clear understanding of required competencies and standards. The course blends practical instruction with expert guidance to help participants confidently complete their accreditation submission and advance their professional AI practice.

Instructor: The course lead is Dr Marie Oldfield. Dr Oldfield is CEO of Oldfield Consultancy and a former Senior Lecturer in Practice at LSE. Dr Oldfield is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci); and a Fellow (FIScT) and Advanced Practitioner in Artificial Intelligence (APAI).

Code: NE25PA10

Location: In-person or online

Duration: Three days onsite • 12 online sessions

Level: FHEQ Level 5

Prerequisites: Demonstrates understanding of EPAI requirements and can provide examples of some competencies

This advanced programme supports participants pursuing FractAI's RPAI professional accreditation. The course deepens understanding of responsible AI practice, required competencies, and professional standards. Through expert-led teaching and tailored mentoring, learners refine their skills and complete their accreditation submission with confidence, strengthening their capability to deliver accountable and trustworthy AI solutions.

Instructor: The course lead is Dr Marie Oldfield. Dr Oldfield is CEO of Oldfield Consultancy and former Senior Lecturer in Practise at LSE. Dr Oldfield is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci); and a Fellow (FIScT) and Advanced Practitioner in Artificial Intelligence (APAI).

Code: NE25PA20

Location: In-person or online

Duration: Three days onsite • 12 online sessions

Level: FHEQ Level 6

Prerequisites: EPAI qualification or demonstrates understanding of RPAI requirements and can provide examples of some competencies

This advanced programme is designed for professionals holding FractAI's APAI accreditation. It strengthens high-level expertise in artificial intelligence, focusing on enhancing the skills, reflective practice, and practical application. Learners receive targeted guidance to deepen capability, refine judgement, and maintain excellence as senior AI practitioners operating at the highest professional standard.

Instructor: The course lead is Dr Marie Oldfield. Dr Oldfield is CEO of Oldfield Consultancy and a former Senior Lecturer in Practice at LSE.  Dr Oldfield is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci); and a Fellow (FIScT) and Advanced Practitioner in Artificial Intelligence (APAI).

Code: NE25PA30

Location: In-person or online

Duration: Two days onsite • 8 online sessions

Level: FHEQ Level 7

Prerequisites: APAI accreditation.

This beginner-friendly course introduces participants to artificial intelligence and machine learning, explaining how systems are built, assessed and used responsibly. Delivered in a non-technical format with discussions and case studies, it covers core concepts, risks, ethical considerations and practical examples to help learners confidently understand and navigate today’s AI-driven world.

Instructor: The course is lead by Dr Marie Oldfield supported by Dr Richard Saldanha. The course lead is Dr Marie Oldfield. Dr Oldfield is CEO of Oldfield Consultancy and former Senior Lecturer in Practise at LSE.  Dr Oldfield is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci) and Advanced Practitioner in Artificial Intelligence (APAI).

Dr Saldanha is a Visiting Lecturer in machine learning at Queen Mary University of London on its master's degree programme in the School of Economics and Finance, a member of the AI for Control Problems Project at The Alan Turing Institute, and a practical user of AI/ML commercially with Oxquant. Dr Saldanha holds a doctorate (DPhil) in Statistics from the University of Oxford. He is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci); and a Fellow (FIScT) and Advanced Practitioner in Artificial Intelligence (APAI).

Code: NE25AI10

Location: In-person or online

Duration: Two days onsite • 8 online sessions

Level: None

Prerequisites: Some basic knowledge of probability and statistics would be useful. Prior knowledge of interpreted languages such as R or Python would be advantageous but is not essential.

This course explores the core components of modern AI systems, including mathematical optimisation, large language models, generative techniques, agentic AI and MLOps. Building on foundational concepts, it helps participants understand how advanced AI methods work in practice and how they are applied across real-world systems, models and development pipelines.

Instructor: The course lead is Dr Richard Saldanha. Dr Saldanha is a Visiting Lecturer in machine learning at Queen Mary University of London on its master's degree programme in the School of Economics and Finance, a member of the AI for Control Problems Project at The Alan Turing Institute, and a practical user of AI/ML commercially with Oxquant. Dr Saldanha holds a doctorate (DPhil) in Statistics from the University of Oxford. He is a Fellow and Chartered Statistician (CStat) of the Royal Statistical Society; a Science Council Chartered Scientist (CSci); and a Fellow (FIScT) and Advanced Practitioner in Artificial Intelligence (APAI).

Code: NE25AI20

Location: In-person or online

Duration: Three days onsite • 12 online sessions

Level: FHEQ Level 6

Prerequisites: This course builds upon the topics introduced by AI10. Some knowledge of probability and statistics is essential. Course participants should also be familiar with linear algebra and basic calculus. Prior knowledge of interpreted languages such as R or Python would be a definite advantage.