University of Wales, Swansea

What you'll study

The curriculum covers foundations of financial markets and risk, quantitative methods, and applications of big data in finance. Digital technology is embedded across modules: students gain hands‑on experience with programming and data tools (for example Python and SQL) and with data visualisation platforms, working with real financial datasets through programming workshops, data analytics labs and case‑based learning.

Entry requirements

The programme is a conversion course and welcomes graduates from any discipline. The school states that applicants are considered on their own merits and that a range of qualifications is accepted; applicants should consult the university for specific academic and English language requirements.

Career prospects

Graduates are targeted at roles that translate complex data into business and financial strategy. Typical job titles cited include financial analyst, data scientist, quantitative analyst, business intelligence manager, risk analyst and machine learning specialist. Employers span finance and banking, fintech, consulting, healthcare, e‑commerce, manufacturing, government and energy. The programme highlights ACCA accreditation and links with professional bodies (CFA Institute, Chartered Banker Institute, CIMA, CISI, ICAEW) as career advantages.

Scholarships & funding angle

The course page does not list specific scholarships. Prospective students should check Swansea University’s central scholarships and bay campus funding pages and enquire about funding, tuition fee status and any professional‑body or institute membership benefits (for example CQF Institute membership) that may offer resources or discounted training.