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Computer Science—Data Analytics (MSc)
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 an acute global shortage of talent and expertise in Data Analytics and Data Science. Due to the strong demand for these graduates and the leading edge quality of this particular programme, annual demand for places on the programme is extremely competitive.
This is an advanced MSc programme that is delivered full-time over one year, and provides graduates of Computer Science and closely related areas with in-depth knowledge and skills in the emerging growth area of Data Analytics and Data Science. The MSc in Data Analytics is delivered by a team of highly respected academics based in University of Galway that are considered international experts in their respective fields. Some of the topic areas include large-scale data analytics, advanced data-mining and machine learning, deep learning, information retrieval, natural language processing, data visualisation, web mining, linked-data analytics, simulation and modelling, and digital image processing.
This programme is aimed at graduates with a primary qualification in Computer Science or related subject area. It is not a conversion course, and students are expected to be already at a very high technical standard with regard to the technical elements of their computing background.
In addition to completing a range of advanced modules, students will then reinforce their newly gained skills through a 30-credit project that is completed during the summer and evaluated through a thesis (minor dissertation) format. For these projects, students work directly with an academic supervisor in their chosen area of specialisation, while they also can pursue the opportunity to collaborate with a research groups across University of Galway or with an industry partner.
The School of Computer Science Advanced MSc Scholarship (Artificial Intelligence, Data Analytics)
University of Galway, School of Computer Science is offering one scholarship for the MSc in Computer Science (Artificial Intelligence, Data Analytics) commencing the next academic year; this scholarship, up to the full value of the EU tuition fee is awarded to the highest ranked graduate of the BSc Computer Science & IT undergraduate programme (GY350) among those who apply for the scholarship. This is open to all current GY350 final year students due to graduate in the current academic year, and all previous graduates of the programme. Please note that to be considered for this merit-based scholarship, applicants must first apply and be accepted to their chosen programme. They will subsequently be required to complete a separate scholarship application form.
Other scholarships available
Find out about our Postgraduate Scholarships here.
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You may also be interested in one of our other School of Computer Science postgraduate programmes.
Applications and Selections
Applications are made online via the University of 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
- Dr Frank Glavin—Programme Director
- Professor Paul Buitelaar
- Professor Jim Duggan
- Dr Conor Hayes
- Dr John McCrae
- Dr James McDermott
- Dr Matthias Nickles
- Dr Colm O'Riordan
- Dr Ihsan Ullah
- Professor Michael Madden
- Dr Nicola Fitz-Simon
- Dr Emma Holian
- Dr Kevin Jennings
- Dr Brian Deegan
- Professor Michael Tuite
- Professor John Newell
Requirements and Assessment
Key Facts
Entry Requirements
Prior Qualification: this MSc is targeted at high-performing graduates of Level 8 (or equivalent) computer science programmes, or Level 8 (or equivalent) science/ engineering programmes that offer sufficient training in computing. The minimum academic requirement for entry to the programme is a First Class Honours (or equivalent) from a recognised university or third-level college. However, a good Second Class Honours (or equivalent) can be deemed sufficient on the recommendation of the Programme Director.
English Language Proficiency: Overall, entry to the MSc requires a minimum IELTS score of 6.5 in writing, with no less than 6.0 in any other band. TOEFL: Overall 88, Listening 12–19, Speaking 18–19, Writing 24–26, Reading 13–18. PTE: 61 overall, no less than 61 in writing, and no less than 50 in any one other component.
Additional Requirements
Recognition of Prior Learning (RPL)
Duration
1 year, full-time
Next start date
September 2025
A Level Grades ()
Average intake
50
QQI/FET FETAC Entry Routes
Closing Date
Please refer to the offer rounds/closing date web-page.
NFQ level
Mode of study
ECTS weighting
90
Award
CAO
Course code
MSC-CSD
Course Outline
The MSc is a 90-ECTS course with three main elements: core modules (40 ECTS), optional modules (20 ECTS), and a substantial capstone thesis project (30 ECTS).
Core modules include: Information Retrieval, Introduction to Natural Language Processing, Principles of Machine Learning, Programming for Data Analytics, Deep Learning, Web and Network Science, Data Visualisation, Case Studies in Data Analytics
Optional modules include: Tools & Techniques for Large Scale Data Analytics, Modelling I, Statistics for Data Science 1, Applied Statistics I, Systems Modelling and Simulation, Discrete Mathematics, Knowledge Graphs, Advanced Topics in Natural Language Processing, Statistics for Data Science 2, Embedded Image Processing, Applied Statistics II
From Semester 2 onwards, students work on individual projects and submit them in August. Projects may have a research or applied focus.
Further Education
- This is a distinctive programme that is closely aligned to the research and teaching expertise of the School of Computer Science and the Digital Science Institute in University of Galway.
- Graduates of this programme are waived a year from their studies on the University of Galway Structured PhD Programme in Computer Science to reflect their completion of advanced computing modules through the MSc Data Analytics.
- Demand for graduates from this programme in industry is very strong both locally, nationally and internationally.
- Due to the nature of this programme, it is seen as the almost perfect preparation and route into a PhD in Machine Learning, Artificial Intelligence or Data Analytics/Science. Graduates from this programme have been hugely successful in pursuing highly prestigious and competitive PhD Scholarships as a result of their MSc Data Analytics qualifications. Many of these graduates can then pursue careers in research and development, academia and a host of consulting and leading industry roles.
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, Paddypower.com, Merck Pharmaceuticals as well as many specialised companies and start-ups.
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 University of 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
Transferable Skills Employers Value
Work Placement
Study Abroad
Related Student Organisations
Course Fees
Fees: EU
Fees: Tuition
Fees: Student levy
Fees: Non EU
For 25/26 entrants, where the course duration is greater than 1 year, there is an inflationary increase approved of 3.4% per annum for continuing years fees.
Postgraduate students in receipt of a SUSI grant – please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2025/26). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.
Note to non-EU students: learn about the 24-month Stayback Visa here.
Find out More
Programme Administrator
E: MScCS-DA@universityofgalway.ie
What Our Students Say
Xue Yang | Student
Firstly I completed the MSc in Information Systems Management at NUI Galway and became interested in IT after that. I decided to choose the MSc in Computer Science (Data Analytics) to transfer my major from business to IT for further study. The MSc in Data Analytics is a program involving many AI-related courses such as machine learning, deep learning, natural language processing, etc. All the lecturers are very knowledgeable and responsive. I learned a lot and it inspired me to dive deep into AI research. I would highly recommend this program to anyone who is interested in AI and data science and wants to be competitive in this area. I won the best ITAG Cyber student project award for my master's project supervised by Dr. Michael Schukat and Dr. Enda Howley. The project is about applying reinforcement learning to the FlipIt security game, which is also a starting point of my PhD research. Winning this award is a huge encouragement to me. I believe the area of using AI technologies to solve Cybersecurity problems is very promising. I appreciate the guidance of my supervisors very much. This is also an award for our team.