Machine Learning for Finance

Key programme benefits to future students

This is an interdisciplinary programme which blends applied, practical financial theory with an advanced technical skillset derived from computer science.



The programme leverages the experience, knowledge and expertise from the industry-led MSc in Artificial Intelligence and provides a focussed upskilling initiative addressing widening AI skills shortage in the financial services industry.



Semester by semester there is a confirmed and measurable achievement of learning objectives that can be transferred directly and immediately to the workplace.



Key Fact: Unique, flexible, online programme at the cutting edge of quantitative finance and computer science. Employment sponsored applicants may receive co-funding by the ICBE Advanced Productivity Skillnet.

Year 1

Autumn Modules

• Introduction to Scientific Computing for AI

• Capital Markets & Corporate Finance



Spring Modules

• Data Analytics

• Derivative Markets



Summer Modules

• Advanced Topics Seminars and Project Specification

• Risk, Ethics, Governance and Artificial Intelligence



Year 2

Autumn Modules

• Project Management in Practice

• Machine Learning for Finance



Spring Modules

• Deep Learning for Finance

• Artificial Intelligence and Machine Learning



Summer Modules

• Project & Dissertation - Machine Learning for Finance

Applicants must hold a Level 8 honours degree at a minimum second class honours, grade 2 (NQF or other internationally recognised equivalent) in a relevant discipline such as finance, economics, business, engineering, computing, mathematics, science or technology.



Applicants from other disciplines who have relevant mathematics and computing elements in their primary degree will also be considered.



Applicants who possess an honours degree, minimum 2nd class, grade 2, or equivalent in a non-numerate discipline and have three years experiential learning in an appropriate computing discipline will be considered.



RPL (Recognised Prior Learning) entry will be available for those who do not meeting the minimum entry requirement but who have gained substantial experience in the area.

2 years part-time, online.

Autumn

Graduate careers

Quantitative Analyst, Financial Analyst, Trader, Data Scientist, Quantitative Engineer, Portfolio Manager, Research Analyst, Data Analyst.