Data Science and Statistical Learning

Entry requirements

• Applicants should hold a bachelor’s degree (NFQ Level 8) with at least a second-class honour, grade 2 (2:2) in Mathematics, Statistics, Physics or a relevant quantitative discipline with a strong mathematical or statistical component.

• You must have and will only be considered if you have a strong foundation in mathematics from a prior programme of study, where they have excelled in their mathematical subjects.

• The university may shortlist and invite you to an interview.

• Previous experience of statistical programming is an advantage but is not required.

Months of entry

September

Course content

UL’s Master of Science (MSc) in Data Science and Statistical Learning delivers focused training in statistical modelling, scientific computing, and data analytics with a statistical emphasis.

Designed to meet the growing global demand for skilled data scientists, the course delivers core competencies including data visualisation, database management, predictive algorithms, and network analysis.

This programme is distinct from computer–science-focused or engineering-focused Data Science degrees. As this is Data Science and Statistical Learning, it places a strong emphasis on the mathematical and statistical foundations of data science and is only suited to those with a solid background in these areas.

There are two pathways available:

Pathway A is the main statistical learning and data science route, designed for most students.

Pathway B is intended for those who have already studied substantial statistical data science content as part of a previous degree (for example, UL mathematics graduates who followed the statistics route).

*Please note:* This is a highly competitive and specialist programme. To succeed, students must have a strong foundation in mathematics from previous studies and should already have demonstrated excellence in mathematical subjects.

To ensure students can successfully complete the programme and to avoid disappointment, we unfortunately do not consider applications that do not meet these requirements.

• Build core skills in statistical modelling, data visualisation, programming, database management, and predictive analytics.

• Transition into careers in data science and analytics across diverse industries with targeted, industry-relevant training.

• Get hands-on experience in scientific computation, data manipulation, interrogation, network analysis, and machine learning.

• Prepare for careers in diverse sectors such as tech, finance, pharmaceuticals, and research, or for progression to PhD programmes.

• Gain hands-on experience through a research project and MSc dissertation, with a focus on applied data science.

Information for international students

• Postgraduate Entry Requirements for International Students
• English Language Requirements

Email ULGlobal@ul.ie for further information.

Fees and funding

• Scholarships for International Students
• Sports Scholarships