Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: 1 year full-time - mulitple intakes
This course is designed for non-specialists to explore the evolving relationships among corporations, financial markets and investors. Course content combines financial theory, AI approaches and hands-on learning with tools like Python and MATLAB coding programmes to prepare you for a dynamic financial landscape.
Key course content includes:
Artificial intelligence in fintech: AI applications in fintech
Governance and sustainability: the financial and ethical challenges facing modern corporations
Econometric modelling: statistical techniques of estimation, hypothesis testing and modelling
Big data analytics using Python: understand and apply various knowledge representation approaches that are available for organising different data types, including structured data (fundamental/or analytical data) vs unstructured data (such as financial news and media news).
Start dates:
An honours degree 2:2 or above in any discipline or appropriate work experience in the financial sector together with relevant professional qualifications.
We recognise a breadth of qualifications; speak to one of our advisers today to find out how we can help you.
On successful completion, you will be able to:
demonstrate a critical understanding of financial theories and principles, and the ability to constructively challenge their assumptions.
Appraise financial risk and associated risk management strategies to identify appropriate applications and limitations of portfolios and derivative instruments to manage risk exposure.
Evidence the application of advanced mathematical and statistical methods for financial analysis, interpretation and decision-making.
Demonstrate critical awareness of the role and importance of effective corporate governance, ethical responsibility, professional accountability, civic contribution, and sustainability.
Execute research using critical judgement in the selection of methodological approaches, financial frameworks, research techniques, and tools, and apply procedures to real-world finance scenarios.
Demonstrate a comprehensive understanding of FinTech and its relevance for financial institutions and markets.
Perform Python coding, computing techniques and machine learning to extract meaningful information and patterns from large supervised and/or unsupervised data sets.
Critique the ramifications of artificial intelligence for contemporary financial systems.
Artificial Intelligence in FinTech - 30 credits
Big Data Analytics using Python — 30 credits
Data Analysis and Research Methods — 30 credits
Corporate Finance and Risk Management — 30 credits
Governance, Ethics and Sustainability — 30 credits
Postgraduate Project — 30 credits
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