To help you best prepare for your MSc, your Programme Director has identified some pre-reading materials which will give you a head start on your programme.

Preparatory materials

This Resource List provides students with preparatory materials for the programme. You will also find some optional readings that give you a broad overview of academic research on FinTech.

Access the Resource List

Mathematics

Some of the courses on programme are mathematically demanding. This is particularly true for Introductory Applied Machine Learning, which is regarded by many students as the most demanding course in the programme. Thus, it is important to review relevant concepts from calculus, linear algebra, and probability theory. The document in the above resource list titled 'Maths in IAML' provides a list of topics and concepts of which you should be familiar.

While you are free to use a range of texts to review this material, you may find it helpful to work through a free MOOC to do this in a structured and efficient manner. There are a number of such MOOCs available on sites like Coursera.

You may also find the 3Blue1Brown YouTube videos on 'The Essence of Linear Algebra' to be helpful for building an intuition for matrix and vector operations.

Finance

For students with little or no academic background in Finance the following book would be useful to purchase (see particularly Chapters 1–9, 11–13, and 22–24):

  • Brealey, Richard A. Fundamentals of Corporate Finance, 10th Edition (2020). (McGraw Hill Education: New York). ISBN: 9781260566093.

FinTech and Policy

To develop an intuition for the policy related issues at the heart of FinTech, please review the following two reports:

You will also find links to these reports in the Resource List above.