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 should hold a bachelor’s degree (NFQ Level 8) with at least a second-class honour, grade 2 (2:2) in the following disciplines: 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.



Other Entry Considerations:



We encourage you to apply even if you don’t meet the standard entry requirements, as long as you can show that you have the knowledge, skills, and experience needed for the programme.





At UL, we value all kinds of learning and support different ways to qualify through our Recognition of Prior Learning (RPL) policy.

2 years part-time, online.

Autumn

Graduate careers

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