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.