- Demonstrate in-depth knowledge of the key skills required by a practicing data scientist, including data collection methods, statistical method development, knowledge and application of machine learning and AI techniques
- Ability to present technical material at a level appropriate for any audience
- Proficiency in data science programming in R and Python
- The ability to create scientific visualisations to explore, summarise, and interpret complex datasets
- Approach problems in an analytical, precise and rigorous way
- Model a broad variety of real-world problems in a statistical framework
- Prove ability to build and maintain web-based data science applications
This course is available through the following application route(s)
This online-delivered Masters Degree course is designed to provide you with all the essential skills of the modern data scientist, including data handling, programming, machine learning, AI methods and advanced statistical analysis. There is an increasing demand for graduates with these valuable skills in a wide range of industries, and currently a shortage of qualified graduates. There are no lectures to attend in person as the courses are delivered completely online by staff of the School of Mathematics and Statistics.
Students will learn through video classes, online demonstrations, and interactive data analysis and coding projects, with regular feedback and interaction with course tutors. This provides flexibility to students who can learn wherever they like at a pace that suits them. Students are required to take in-person examinations at the end of the second trimester of year 1. All other assessments will be completed online.
For detailed information about the programme email dataanalyticsonline@ucd.ie with any queries.
About This Course
Data Science graduates are in strong demand from industry; those who are successful in completing the course are highly employable in fields as diverse as pharmaceuticals, finance and insurance, as well as cloud computing. Some examples of prospective employers include:
- ICT companies (e.g., Google, eBay, Meta, Amazon, Paddy Power)
- The pharmaceutical industry (e.g., Janssen, MSD, GSK)
- The financial services industry (e.g., Bank of Ireland, AXA, EY, Accenture, Deloitte)
Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information.
Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.
| Trimester | Credits | |||
|---|---|---|---|---|
Core modules: STAT40720 Intro Data Analytics (Online) STAT40730 Data Prog with R (Online) STAT30280 Inference for Data Analytics (online) STAT40750 Statistical Machine Learning (Online) STAT40740 Multivariate Analysis (Online) STAT40790 Predictive Analytics I (online) STAT40800 Data Prog with Python (online) STAT40850 Bayesian Analysis (online) STAT40970 Machine Learning and AI 3 x Data Science Project modules across two years of study Option modules: STAT40770 Adv Pred Analytics (online) STAT40810 Stochastic Models (online) STAT40960 Statistical Network Analysis (Online) STAT40830 Adv Data Prog with R (online) *Curricular information is subject to change. |
- This programme is intended for applicants with a degree in a numerate subject. An upper second class honours or international equivalent is required. Those without this requirement, but with equivalent experience in industry, will also be considered on a case by-case basis, or can apply for the Professional Certificate in Mathematics for Data Analytics and Statistics which leads directly into the Data Science programme.
- Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element of the Academic version), or equivalent.
School of Mathematics and Statistics Application Process FAQ
These are the minimum entry requirements – additional criteria may be requested for some programmes
You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage.
Part Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants: Yes
How to Apply
General application route(s) for Irish/UK/EU applicants* for International (non-EU) applicants* to Data Science:
| ROWCLASS | Apply to |
|---|---|
| showAudience-audienceEU showAudience-audienceInt | F275 Data Science Master of Science Part-Time Commencing September 2025 Graduate Taught |
* you can change options at the top of the page