Big Data for Financial Professionals
Queen Mary University of London · England · ECN303
Big Data for Financial Professionals is a subject at Queen Mary University of London, England. It covers topics like big-data, business-analytics, business-intelligence, data-analytics. It is part of 1 degree. The information below is compiled from public course material — approximate, not official.
Queen Mary University of London
ECN303
3.00
Topics covered
Degrees that include Big Data for Financial Professionals
Frequently asked questions
What is Big Data for Financial Professionals about?
Big Data for Financial Professionals covers topics like big-data, business-analytics, business-intelligence, data-analytics.
Which degrees include Big Data for Financial Professionals?
Big Data for Financial Professionals is part of 1 degree, including Applied Finance BSc(Econ).
How many credit points is Big Data for Financial Professionals?
Big Data for Financial Professionals at Queen Mary University of London is typically around 3.00 credit points. Approximate — confirm with the university.
Where is Big Data for Financial Professionals taught?
Big Data for Financial Professionals is taught at Queen Mary University of London, England.
Studying Big Data for Financial Professionals?
Peernovo helps students research, choose and thrive at university — across Australia, the US, the UK and Canada — powered by our AI backbone:
- Explore & compare degrees — across universities and countries with honest, specific information.
- "What Can I Be?" career guidance — an AI pathway councillor that maps degrees to careers.
- See who's studying — your degree at your university — find classmates and study groups.
- AI Task Coach — a Socratic study companion that plans your work around your life.
- Honours & Thesis Research Coach — structure and move your research project forward.
- Smart study planner, exam prep and a daily digest — to keep you on track.
Sources: Queen Mary University of London public course catalogue. Information is compiled and summarised — not copied verbatim — and is approximate; always confirm with the original source.
Something not right on this page, or want it changed? Let us know and we'll review it.