Data Analytics

Key programme benefits to future students

How to apply human factors and ergonomic principles.



Tools to communicate business insights that will empower you to make strategic recommendations using R-Shiny data visualisations and digital dashboards.



A strengthened ability to analyse, summarise, visualise, and report on insights extracted from a dataset using real-world examples from your organisation.

Autumn Modules

• Introduction to Predictive Analytics

• Data Analytics with R (M)

• Future-Focused Professional Portfolio 1



Spring Modules

• Statistical Learning with Applications

• Advanced Predictive Analytics

• Future-Focused Professional Portfolio 2



Summer Modules

• Research Project

Students will specialise their dissertation studies in one of the three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems.

Applicants should typically hold a bachelor’s degree (NFQ Level 8) with at least a second-class honour, grade 2 (2:2) in a related discipline.

and/or



You should have at least 5 years of relevant industry or workplace experience.

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

1 year part-time, on-campus.

Spring

Graduate careers

“Learnings are immediately applicable from the business perspective & have an impact on our ability to deliver high value solutions to customers across the wide range of industries & markets we support.” Rosemary Ryan, Analog Devices