The MSc in Mathematical Modelling provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions.

The programme is aimed at students with a background in a highly numerate discipline who wish to advance their mathematical modelling skills. Successful students will be well placed to satisfy the growing demand for mathematical modelling in commerce and industry, and will learn and practise the skills necessary to pursue further research. This MSc enables students to consolidate their mathematical knowledge and formulate basic concepts of modelling before moving on to case studies in which models have been developed for issues motivated by industrial, biological or environmental considerations.

Data science brings together computational and statistical skills for data-driven problem solving. The MSc in Data Science programme will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking. The programme combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students will take one compulsory module and up to two additional modules in Computer Science, with the remaining modules (including the research project) taken mainly from within Statistical Science.

Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, commerce and medicine. The quantitative skills training provided by the MSc in Statistics can lead to new and exciting opportunities in industry, healthcare, government, commerce or research. The programme takes a broad-based approach to statistics, providing up-to-date training in the major applications and an excellent balance between theory and application. It covers modern ideas in statistics including applied Bayesian methods, generalised linear modelling and object-oriented statistical computing, together with a grounding in traditional statistical theory and methods.

Help define the next wave of change that machine learning will deliver through one of the most established Master’s programmes in this field. The Machine Learning MSc offers opportunities to focus on specific areas of interest in machine learning, including modules run in collaboration with the esteemed Gatsby Computational Neuroscience Unit and Google DeepMind. Taught at UCL, world-renowned for computer science research and breakthroughs, this is an exceptional place to build your expertise in machine learning. 

Tackle emergent challenges through this one-of-a-kind MSc programme that brings the technical side of Artificial Intelligence (AI) together with environmental and humanitarian issues. This is an incredible opportunity to find solutions to pressing problems in sustainable development. Taught at UCL, an international home of AI breakthroughs, this programme places graduates at the heart of a rapidly growing sector. 

Become a changemaker in the world of data science and machine learning through one of the most established Master’s programmes in this field. The Data Science and Machine Learning MSc offers opportunities to study modules that span from artificial intelligence and deep learning to digital finance and probabilistic modelling, enabling you to craft a future career in a range of fields. 

Deepen your expertise in machine learning and statistics through one of the most established Master’s programmes in this field. The Computational Statistics and Machine Learning MSc brings together vital knowledge in both subjects, enabling you to thrive as an expert in a data rich world. With opportunities to study modules run in collaboration with the esteemed Gatsby Computational Neuroscience Unit and Google DeepMind, this is an exceptional place to build your expertise. 

This unique, interdisciplinary programme will teach students how Artificial Intelligence (AI) can have a transformative effect on biomedicine and healthcare. This MSc enables you to develop complex technical skills and use them to craft forward-thinking biomedical and healthcare solutions powered by AI. Taught at UCL, an international home of AI breakthroughs and medical excellence, graduates of this programme will be equipped with sought-after specialist skills, ideal for a rapidly growing sector. 

Gain in-depth expertise in the rapidly growing robotics and artificial intelligence field through this cutting-edge programme. The Robotics and Artificial Intelligence MSc draws together teaching from Computer Science, AI and Electronic and Mechanical Engineering, combining theory with hands-on experience. Our goal is to help you become future engineers, leaders and researchers in intelligent robotics, artificial intelligence, technology, engineering and finance. 

This programme offers research supervision across a broad range of pure and applied mathematics. General areas of expertise in pure mathematics include analysis, geometry, number theory and topology. In applied mathematics key areas of activity include fluid dynamics, mathematical modelling, mathematical physics, mathematical biology, applied and numerical analysis and financial mathematics.

The research degree programme is aimed at graduate students in mathematics or related sciences. Applicants will have analytical skills, and have formed a strong interest in pursuing mathematical research.

More information can be found here.

The Statistical Science research programme at UCL aims to develop research students who can eventually make original contributions to the subject. Students are initially registered for the MPhil degree. No sooner than one year, they are transferred to the PhD degree with retrospective effect if they show a capacity for original work. The typical length of the PhD programme is three years for full-time students and five years for part-time students; an MPhil might be achievable in less.

More information can be found here.

This integrated four-year programme is a joint CDT between UCL and Imperial College. The CDT focuses on research on the interface of computational mathematics, data sciences and research software engineering. The creation of future digital twins and other types of simulations that mix physics and data-based approaches does not only require skills across the mathematical and data sciences but also significant software engineering knowledge. This CDT trains students on the interface of these disciplines so that our graduates can fluently move across data, computational modelling, and software design decisions to react and lead on the development of future simulation technologies that are the core of important challenges, such as fusion energy, climate, or digital health.

More information can be found here.