Course Overview

Almost everything we do results in data being created and stored somewhere. Individuals, communities, business and governments face major challenges in harnessing all this data to create knowledge that will underpin a healthier, safer, more productive world. There is a global shortage of talent and expertise in Data Analytics and Data Science.

This MSc programme will provide graduates of Computing or related degrees with the deep technical knowledge and analytical skills to succeed in this growth area.

 Applicants may apply for the following programme options:

  • 1-year MSc full-time 
  • 2-year MSc part-time. More information on the part-time option for this programme can be found here. 
  • 1-year Diploma. More information on the part-time option for this programme can be found here.

This is an advanced MSc programme that provides graduates of Computer Science and closely related areas with in-depth knowledge and skills in the emerging growth area of Data Analytics. It includes topics such as large-scale data analytics, advanced data-mining and machine learning, applied regression modelling, information retrieval techniques, natural language processing, data visualisation, Web mining, Linked-Data analytics, simulation and modelling, digital image processing. 

The course provides several foundational modules in topics such as probability and statistics and  programming techniques for data analytics. Students on the programme further deepen their knowledge of data analytics and science by working on a project either in conjunction with a research group or with an industry partner. 

Scholarships available
Find out about our Postgraduate Scholarships here.

Applications and Selections

Applications are made online via the NUI Galway Postgraduate Applications System

Application requirements:

  • A personal statement
  • A CV
  • University Degree Transcripts
  • Two references
  • IELTS/TOEFL certificate—only if English is not your mother tongue

What is not required (please do not submit these)

  • secondary school certificates
  • training certificates
  • membership certificates

Who Teaches this Course

Requirements and Assessment


Key Facts

Entry Requirements

This MSc is targeted at high- performing graduates of level 8 computer science programmes or level 8 science or engineering programmes that offer sufficient training in computing. Eligibility will be determined by the programme director. The minimum requirement for entry to the full-time and part- time programme is normally a 2.1 degree. Additionally, part-time applicants should have 3+ years of relevant industry experience and availability to attend lectures in NUI Galway. 

More information on the part-time option for this programme can be found here.

On an exceptional basis, candidates who do not meet the requirements stated above but are deemed by the programme director to have reached an equivalent standard may also be considered. 

English Language Requirement, MSc full-time, 1 year: Overall, entry to the Data Analytics MSc GYE06 programme requires a minimum score of 6.5 IELTS, with  no less than 6.5 in the writing ability category and no less that 6 in the other categories.

Additional Requirements


1 year, full-time

Next start date

September 2020

A Level Grades ()

Average intake


Closing Date

Please refer to the offer rounds/closing date webpage.

NFQ level

Mode of study

ECTS weighting




Course code


Course Outline

The MSc option is an 90-ECTS course with three main elements: foundational modules (20 ECTS), advanced modules (40 ECTS), and a substantial capstone project (30 ECTS).

Foundational modules include: modules in Statistics & Probability; Machine Learning and Data Mining; Programming for Data Analytics; Tools and Techniques for Large Scale Data Analytics; Applied Regression Modelling; Digital Signal Processing.

Advanced modules include: Advanced Topics in Machine Learning and Information Retrieval; Natural Language Processing; Web-Mining; Linked-Data Analytics; Modern Information Management; System Modelling & Simulation; Embedded Image Processing; Data Visualisation and Case Studies in Data Analytics.

From Semester 2 onwards, students work on individual projects and submit them in August. Projects may have a research or applied focus. 

Curriculum Information

Curriculum information relates to the current academic year (in most cases).
Course and module offerings and details may be subject to change.

Glossary of Terms

You must earn a defined number of credits (aka ECTS) to complete each year of your course. You do this by taking all of its required modules as well as the correct number of optional modules to obtain that year's total number of credits.
An examinable portion of a subject or course, for which you attend lectures and/or tutorials and carry out assignments. E.g. Algebra and Calculus could be modules within the subject Mathematics. Each module has a unique module code eg. MA140.
Some courses allow you to choose subjects, where related modules are grouped together. Subjects have their own required number of credits, so you must take all that subject's required modules and may also need to obtain the remainder of the subject's total credits by choosing from its available optional modules.
A module you may choose to study.
A module that you must study if you choose this course (or subject).
Required Core Subject
A subject you must study because it's integral to that course.
Most courses have 2 semesters (aka terms) per year, so a three-year course will have six semesters in total. For clarity, this page will refer to the first semester of year 2 as 'Semester 3'.

Year 1 (90 Credits)

Optional ST1100: Engineering Statistics - 5 Credits - Semester 1
Optional MA204: Discrete Mathematics - 5 Credits - Semester 1
Optional ST235: Probability - 5 Credits - Semester 1
Optional CT475: Machine Learning & Data Mining - 5 Credits - Semester 1
Optional MP305: Modelling I - 5 Credits - Semester 1
Optional EE445: Digital Signal Processing - 5 Credits - Semester 1
Optional MA215: Mathematical Molecular Biology I - 5 Credits - Semester 1
Optional CT561: Systems Modelling and Simulation - 5 Credits - Semester 1
Optional CT422: Modern Information Management - 5 Credits - Semester 1
Optional ST313: Applied Regression Models - 5 Credits - Semester 1
Optional CT5105: Tools and Techniques for Large Scale Data Analytics - 5 Credits - Semester 1
Optional CT5119: Functional Programming for Data Analytics - 5 Credits - Semester 1
Required CT5120: Introduction to Natural Language Processing - 5 Credits - Semester 1
Optional CT5108: Data Analytics Project - 30 Credits - Semester 1
Optional DER5101: Linked Data - 5 Credits - Semester 2
Optional CT5107: Advanced Topics in Machine Learning and Information Retrieval - 5 Credits - Semester 2
Optional ST412: Stochastic Processes - 5 Credits - Semester 2
Optional MA461: Probabilistic Models for Molecular Biology - 5 Credits - Semester 2
Optional CT5100: Data Visualisation - 5 Credits - Semester 2
Optional ST312: Applied Statistics II - 5 Credits - Semester 2
Optional ST236: Statistical Inference - 5 Credits - Semester 2
Optional EE551: Embedded Image Processing - 5 Credits - Semester 2
Optional CT5113: Web and Network Science - 5 Credits - Semester 2
Optional CT5103: Case Studies in Data Analytics - 5 Credits - Semester 2
Optional CT5121: Advanced Topics in Natural Language Processing - 5 Credits - Semester 2

Further Education

  • This is a distinctive programme that is closely aligned to the research and teaching expertise of the Information Technology discipline and the Insight Centre for Data Analytics in NUI Galway.
  • It will opens the door for graduates  to new career opportunities in industry, in starting new ventures or  in PhD-level research.

Why Choose This Course?

Career Opportunities

Data analytics skills are required in every industry. Graduates will be excellently qualified to pursue exciting careers in national and multinational industries in a wide range of areas. Our graduates currently work for companies as diverse as IBM, SAP, Cisco, Avaya, Google, Fujitsu, Accenture,, Merck Pharmaceuticals as well as many specialised companies and startups.

Opportunities include:

  • The development of  innovative new services and products based on data analytics
  • The development of new types of data analysis services and solutions
  • The creation of leading-edge start-ups that provide analytics solutions and products.
  • PhD-level research in NUI Galway, elsewhere in Ireland, or abroad

 A Career in Data Analytics?  

  • Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future.
  • The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone.
  • CNN has listed jobs in this area in their Top 10 best new jobs in America. 

Scholarships Available
Find out about our Postgraduate Scholarships here.

Who’s Suited to This Course

Learning Outcomes


Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

€7,215 p.a. 2019/20

Fees: Tuition

€6,991 p.a. 2019/20

Fees: Student levy

€224 p.a. 2019/20

Fees: Non EU

€17,750 p.a. 2019/20

 Information on International Scholarships is available here.   

For EU students only 2019/20

1CSD1 full time EU €7,215;

Find out More

Programme Administrator
T: +353 91 493 143


  • Postgraduate Taught Prospectus 2020

    Postgraduate Taught Prospectus 2020 PDF (21 MB)