30Apr
UndergraduateCourse summary
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).
- access a modern Bloomberg Trading Floor, which promotes dynamic learning through real-time data streaming so you can learn the skills needed to work in the finance industry
- develop your industry-relevant skills in Python, MATLAB and LSEG Workspace
- obtain Bloomberg Market Concept (BMC) and Environmental Social Governance (ESG) certifications at no additional cost
- learn from professionals with industry and research experience and interact with expert guest practitioners and scholars of finance (opportunities not guaranteed)
- access career coaching and mentoring to help your career planning and profile development
- apply best practices for AI tools and entrepreneurship in fintech, banking and corporations, and enhance your understanding of privacy, ethics and the fintech regulatory landscape.
Modules
- Artificial Intelligence in FinTech
- Data Analytics Using Python
- Data Analysis and Research Methods
- Corporate Finance and Risk Management
- Governance, Ethics and Sustainability
Assessment method
This course will be assessed using a variety of methods which could vary depending upon the module. Assessment methods may include reports, tests, exams, practical coursework and presentations as part of individual assignments or group work elements. The Coventry University assessment strategy aims to ensure that our courses are fairly assessed and allows us to monitor student progression towards achieving the intended learning outcomes.
Qualified teacher status (QTS)
To work as a teacher at a state school in England or Wales, you will need to achieve qualified teacher status (QTS). This is offered on this course for the following level:
- Course does not award QTS
Entry requirements
Applicants should hold an honours degree 2:2 or above in a relevant academic discipline, such as business, finance, accounting or economics. Or should hold a suitable graduate level (Level 6 equivalent) professional qualification including ACCA, CIMA, CIPFA, CFA, ICAEW and ICAS. Applications from candidates with relevant experience will be considered on an individual basis. We recognise a breadth of qualifications, speak to one of our advisers today to find out how we can help you. We recognise a breadth of qualifications; speak to one of our advisers today to find out how we can help you
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
2025/26 fees TBC. Please see our website for latest information.
Provider information
Coventry University
Priory Street
Coventry
CV1 5FB