Computing for Data Analytics and Finance (854G1)

15 credits, Level 7 (Masters)

Autumn teaching

From basic programming skills with applications in a suitable programming language such as MATLAB/Octave or Python.

While no previous programming experience is assumed we build up quite quickly to an operational level including (tax/loan/investment/portfolio) ledger book programming, graphing and charting financial data, stochastic simulations involving random number generators, importing/exporting to databases and websites, and more advanced topics in financial computing and financial data analysis.

Teaching

30%: Lecture
70%: Practical (Practical, Workshop)

Assessment

50%: Coursework (Portfolio, Problem set)
50%: Examination (Computer-based examination)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 33 hours of contact time and about 117 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.