A minimum of a lower second class honours degree (2:2).
This degree is designed to enable students from different disciplines to change careers and enter the Fintech field. Students are expected to have a background in a numerical subject to cope with the high levels of programming and statistics involved.
Alternative professional qualifications with at least three years of relevant professional experience will also be considered.
If your first language is not English, you should have an IELTS 6.5 overall, with a minimum of 6.0 in each component.
Visit our How to apply page for more information on:
A minimum of a lower second class honours degree (2:2).
This degree is designed to enable students from different disciplines to change careers and enter the Fintech field. Students are expected to have a background in a numerical subject to cope with the high levels of programming and statistics involved.
Alternative professional qualifications with at least three years of relevant professional experience will also be considered.
If your first language is not English, you should have an IELTS 6.5 overall, with a minimum of 6.0 in each component.
Visit our How to apply page for more information on:
Visit our How to apply page for more information on:
Visit our How to apply page for more information on:
It provides detailed coverage of global financial markets, institutions and their services and securities, alongside a thorough introduction to key aspects of FinTech. Encompassing both quantitative and qualitative methods, you'll build your knowledge of business analytics, together with the basic programming skills and analytical techniques required for using computational methods in finance. You’ll learn how to use standard industry-based mathematical and statistical packages and select from the range of analytic techniques to analyse current data accessible via Bloomberg or Data Stream. We also delve into new, more complex emerging technologies, including blockchain, original and new types of cryptocurrencies, artificial intelligence (AI), machine learning (ML) and predictive analysis. You'll gain a detailed knowledge and advanced learning of a range of AI/ML techniques, including logistic regression, decision tree, Naive Bayes and others to solve problems or to undertake projects in capital markets, asset portfolio and risk management contexts. To better prepare you to predict future or unknown outcomes in the financial services sector, you’ll learn about big data management, data mining methods and decision-support in a variety of financial services contexts, such as corporate finance, forecasting in capital markets, credit risk, fraud detection and asset management.
This innovative course has been designed for learners who wish to specialise in one of the most exciting areas of finance and gain a deeper understanding of finance applications that are transforming the financial services sector. It provides detailed coverage of global financial markets, institutions and their services and securities, alongside a thorough introduction to key aspects of FinTech.
Encompassing both quantitative and qualitative methods, you'll build your knowledge of business analytics, together with the basic programming skills and analytical techniques required for using computational methods in finance. You’ll learn how to use standard industry-based mathematical and statistical packages and select from the range of analytic techniques to analyse current data accessible via Bloomberg or Data Stream.
We also delve into new, more complex emerging technologies, including blockchain, original and new types of cryptocurrencies, artificial intelligence (AI), machine learning (ML) and predictive analysis. You'll gain a detailed knowledge and advanced learning of a range of AI/ML techniques, including logistic regression, decision tree, Naive Bayes and others to solve problems or to undertake projects in capital markets, asset portfolio and risk management contexts.