MSc Finance and Data Analytics

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Offer response
1 weeks after your application is submitted
Backlogs accepted
This course accepts backlogs

Overview

As the modern financial industry increasingly turns to big data to inform investment decisions, there is a growing demand for professionals with a specialisation in data analytics. This course equips you with data analysis skills that are in short supply and can be utilised in algorithmic trading, machine learning and artificial intelligence applications.

As you study, you’ll develop core skills in finance, investments and data analytics – all of which can be applied in a final dissertation on a finance-related topic of your choice. You’ll also be taught how to use programming languages (e.g. Python, R) to analyse data and get a thorough understanding of core financial theory and investment practices. In addition, you'll have the opportunity to use professional financial databases, such as Bloomberg, Eikon and S&P Capital IQ.

Other features of the course include the Amplify Trading Boot Camp, where you can get first-hand experience of real-world trading, and the Student Managed Investment Fund, which provides experience of managing actual funds through targeted investments. All these features help to enhance employability, give you practical skills, and play a part in a world-leading student experience. Students can also exit with PGCert and PGDip awards.

Course objectives

Over the course of your studies on this Masters course you will:

  • Gain deep understanding of finance theories
  • Acquire skills in programming languages
  • Develop knowledge and skills in analysing data to inform investment decisions
  • Enhance your critical and analytical skills
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Requirements

The requirements may vary based on your selected study options.





















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Use our magical AI system, to check your admission chances for this course.
Tuition fee
Apply by
Start date
Duration
Campus
Mode of study
Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
Offer response
1 weeks after your application is submitted
Backlogs accepted
This course accepts backlogs