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About NUI Galway
About NUI Galway
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Computer Science—Artificial Intelligence (MSc)
Artificial Intelligence is one the most exciting and fastest growing areas of the ICT industry and research. It has the potential to positively transform every aspect of all our lives, from Smart Cities and Autonomous Vehicles, through to improved healthcare services and low-carbon economies. Artificial Intelligence has the capacity to provide intelligent solutions that can help us to tackle many today’s greatest societal challenges.
Become part of this exciting development by joining our one-year MSc in Computer Science—Artificial Intelligence.
This programme is aimed at graduates with a primary qualification in Computer Science or related subject area. It is not a conversion course, but expects students to be already at a very high technical standard with regard to their Computer Science education.
The full-time MSc in Artificial Intelligence is taught by renowned, interdisciplinary NUI Galway experts in the field. It covers over two semesters many complementary areas of Artificial Intelligence, including Meta-Heuristic Optimisation, Deep Learning, Autonomous Agents and Multi-Agent Systems.
Furthermore, students reinforce their newly gained skills in a 30-credit project that is completed during the summer. Here students may have the opportunity to collaborate with a research group or with an industry partner.
Applications and Selections
Applications are made online via the NUI Galway Postgraduate Applications System.
Your online application shall include:
- A personal statement outlining:
- A summary of your primary degree and its relevance for a successful completion of this programme. We strongly encourage an evidence-based approach to highlighting your academic accomplishments.
- A summary of your previous capstone projects (e.g. undergraduate final year projects) including an outline of your exact contribution to these. We strongly encourage an evidence-based approach to outlining your existing technical skills and experience.
- Your 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
Professor Michael Madden
Dr Enda Barrett
Dr Attracta Brennan
Dr Paul Buitelaar
Dr Des Chambers
Dr Jim Duggan
Dr Frank Glavin
Dr Josephine Griffith
Dr Conor Hayes
Dr Seamus Hill
Dr Enda Howley
Dr Eddie Jones
Dr John McCrae
Dr James McDermott
Dr Hugh Melvin
Dr Owen Molloy
Dr Conn Mulvihill
Dr Matthias Nickles
Dr Colm O'Riordan
Dr David O'Sullivan
Dr Sam Redfern
Dr Heike Schmidt-Felzmann
Dr Michael Schukat
Dr Finlay Smith
Requirements and Assessment
This MSc is targeted at high-performing graduates of level 8 computer science programmes, or level 8 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 in Computer Science—Artificial Intelligence requires a minimum IELTS score of 6.5, with no less than 6.5 in the writing ability category and no less than 6.0 in the other categories.
12 months, full-time
Next start date
A Level Grades ()
Please view the offer rounds website.
Mode of study
The MSc in Computer Science—Artificial Intelligence is a one-year 90-ECTS course with three main elements:
- foundational modules (35 ECTS)
- advanced modules (25 ECTS), and
- a substantial capstone project (30 ECTS).
Foundational modules include: Machine Learning and Deep Learning; Natural Language Processing; Information Retrieval; Meta-Heuristic Optimisation; Ethics in Artificial Intelligence; Autonomous Agents and Multi-Agent Systems.
Advanced modules include: Programming and Tools for AI; Knowledge Representation & Statistical Relational Learning; Data Visualisation; Programming for Data Analytics; Web & Network Science; Embedded Image Processing; Tools and Techniques for Large Scale Data Analytics; Research Topics in AI.
From Semester II onwards, students work on individual projects and submit them in August. Projects may have a research or applied focus.[an error occurred while processing this directive]
Why Choose This Course?
AI skills will be required in every industry and could create—according to a recent Forbes report—globally up to 22 million new jobs by 2022. The World Economic Forum estimates that by 2025 machines are expected to perform more current work tasks than humans compared to 71% being performed by humans today, and their recent report concludes that artificial intelligence, robotics and smart automation technology could contribute up to $15 trillion to global GDP by 2030.
Within the AI space, there is a diversity of jobs requiring various levels of expertise:
- More foundational jobs include data architects, software engineers and machine and deep learning engineers.
- Advanced roles include specialist research engineers, including those that specialise in computer vision, language and speech, and AI architects.
Who’s Suited to This Course