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School of Economics and Finance

MSc Finance and Machine Learning

In finance, machine learning has evolved into a key skill for managing assets, assessing risk, calculating credit scores, and approving loans, among other financial services. Today, numerous leading fintech and financial service companies are integrating machine learning strategies into their operations, resulting in better-streamlined processes, reduced risks, and enhanced portfolios.


This course couples solid training on mainstream finance topics with a deep understanding of so-called machine learning methodologies for the analysis of financial markets. This specialists course extends a typical Finance postgraduate course by focusing on the use of statistical learning for investment decisions, risk management, as well as the development and engineering models for the analysis of "Big Data".

  • Provides a strong background in finance
  • Grounding in machine learning methods and how they are used in finance through cutting-edge curriculum
  • The knowledge to implement machine learning tools using Python
  • A learning environment that encourages the development of systematic and independent thought and learning
  • A methodical knowledge of quantitative methods so that you will have the skills necessary to undertake quantitative analyses of relevant problems

Hear from the Programme Director

Dr Daniele Bianchi, Associate Professor in Finance at Queen Mary University of London, provides an overview of the MSc Finance and Machine Learning programme.

Is this course for me?

The taught programme is aimed at two types of audiences. First, to graduate students who wish to pursue their studies in quantitative finance with a view towards risk analytics and investment management. The second target groups are professionals from the financial services industry who either seek to pivot towards methods that are based on machine learning or are simply interested in these new tools and want to upgrade their set of competencies.

Do I need to know Computer Programming?

This taught course is aimed at students with a solid quantitative background which however may not have been extensively exposed to computer programming. If you want to become a specialist in applying machine learning methods in finance, this course will provide the first crucial step towards that goal. Study areas include econometrics, time-series analysis, computer programming, statistical and probability theory, in addition to mainstream topics in finance such as asset pricing, corporate finance and investments.

You'll study in one of the UK's leading research departments, and contribute to our renowned research culture with your own independent project at the end of the course of study. You will benefit from cutting-edge research-led teaching, with the department research strengths, such as asset pricing, financial econometrics and investments.

Hear from our alumni

"I chose to pursue the MSc in Finance and Machine Learning to enhance my skills in data analysis and building machine learning models and algorithms. Having managed a trading desk for an investment management firm, I saw first-hand the importance of analysing the vast amounts of data generated and its potential uses to help improve performance returns for investors. Combined with the use of algorithms to implement trading strategies, this encouraged me to delve deeper into machine learning principles.

This MSc equips me with the essential toolkit to evaluate models and grasp the underlying intuition behind them. This, I believe, sets apart this programme – it's not just about academic teaching, but also places great emphasis on the fundamentals all wrapped within applicable finance and economic scenarios.

As I venture into a new startup in investment management, I recognise the importance of recruiting candidates with a strong background in both machine learning and finance."

Alumni and MSc Finance and Machine Learning Student

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