Taught course

Financial Mathematics and Machine Learning

Queen Mary, University of London · Mathematical Sciences

Entry requirements

A 2:1 or above at undergraduate level in Mathematics or a subject with a strong Mathematics component such as Physics, Engineering or Computer Science.

Find out more about how to apply for our postgraduate taught courses.

Months of entry


Course content

Learn to apply a wide range of mathematical and statistical techniques to model the behaviour of the financial markets.

This programme is designed to equip students with the skills needed for a successful career in the more quantitative areas of banking and financial markets, or in financial mathematics research.

This programme is taught by lecturers with considerable experience in investment banking and financial markets. In addition to learning about modern financial mathematics, you will undertake two modules in machine learning, helping you to stand out in a field that has become immensely important over the last few years.

You will also benefit from a host of extracurricular activities to help develop the key skills sought by financial institutions. For example, as well as the Microsoft Excel Specialist Certification, you will have the opportunity to undertake the prestigious Bloomberg Market Concepts certification via our trading suite.


You will gain a clear understanding of modern financial mathematics and machine learning, together with a range of numerical and computational techniques that form an important part of the toolkit of a typical practitioner.

The programme structure is flexible, so you can choose to focus on computational or mathematical modules, depending on your background, interests and future plans.

You will receive a comprehensive introduction to the field, including the structure of financial instruments and the operations of the markets, foundations of mathematical modelling in finance, tools for machine learning using Python, and introductory computer programming in C++.

Modules include:

  • Advanced Computing in Finance
  • Advanced Derivatives Pricing and Risk Management
  • Advanced Machine Learning
  • Continuous-time Models in Finance
  • Financial Instruments and Markets
  • Financial Mathematics Project and Dissertation
  • Foundations of Mathematical Modelling in Finance
  • Machine Learning with Python
  • Programming in C++ for Finance
  • Topics in Probability and Stochastic Processes

Please note that module offerings may be subject to change.

For the latest information visit our website.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification
    part time
    24 months
    • Campus-based learningis available for this qualification

Course contact details

School of Mathematical Sciences
+44 (0)20 7882 5440