Machine Learning for Finance

University of Limerick

Machine Learning for Finance

Key Fact:
Unique, flexible, online programme at the cutting edge of quantitative finance and computer science.

Subjects taught

Programme Content
Year 1
Autumn Semester
• Introduction to Scientific Computing for AI
• Capital Markets & Corporate Finance

Spring Semester
• Derivative Markets
• Data Analytics

Summer Semester
• Risk, Ethics, Governance and Artificial Intelligence
• Advanced Topics Seminars & Project Specification

Year 2
Autumn Semester
• Project Management in Practice
• Machine Learning for Finance

Spring Semester
• Artificial Intelligence and Machine Learning
• Deep Learning for Finance

Summer Semester
• Project & Dissertation: Machine Learning for Finance

Entry requirements

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.

Application dates

How to apply:
1. Choose your programme.
2. Check closing date for the programme.
3. Apply online at
4. Have your supporting documentation ready to upload.
5. Pay the application fee (€35 online / €40 bank draft or cheque).
6. Submit your application.


Qualification transcripts and certificates

A copy of your birth certificate/passport

If your qualifications have been obtained in a country where English is an official language this will suffice

If this is not available, the following additional documents must be provided:

• English translation of your qualification(s)/transcripts
• English language competency certificate


2 Years Part-Time. Online.

The programme is delivered primarily via recorded online lectures, supported with tutorials, assignments and live webinars. All relevant course material will be available digitally via the UL Glucksman Library online resources.

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Part time

  • Apply to

    Course provider