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Artificial Intelligence (MSc)

  • Course Code


  • Field of Study

    Computing,Computer Science

  • Type of Course:

    Masters Degree

  • Type of Qualification:


  • Type of Study:

    Full time

  • Application Closing Date:

    14th September 2018

Course duration:

One Academic Year

Admission Requirements:

Admission Requirements

Successful applicants will hold at least a second-class honours degree in Computer Science, Computing, Electrical/Electronic Engineering or a cognate discipline. Furthermore, all successful applicants are required to have a proficiency in mathematics, including statistics, and an advanced level of coding competency in a modern high-level computer programming language.



Course summary

Artificial intelligence (AI) is a field of computer science that enables computers and machines to perform tasks normally requiring human intelligence. Its many applications range from chess-playing robots and autonomous cars to speech, image, and language processing, robotic manufacturing, and surveillance systems. In the twenty-first century, AI has experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding. AI techniques have now become an essential part of the technology industry, helping to solve many challenging problems in computer science. This master’s programme provides a technical deep-dive into the area of AI. It aims to produce AI engineers with a highly relevant skillset in AI topics. Students will learn how to use and develop intelligent computer systems that can learn from experience, recognise patterns in vast amounts of data and reason strategically in complex decision-making situations. The programme content will deliver a comprehensive range of topics integral to the study of AI. These include machine learning, deep learning, natural language processing, optimisation, and big data processing to name but a few. The programme contains challenging and interesting modules delivered by lecturers who are experts in AI. Students will be presented with opportunities to work on industry focused projects and research opportunities linked to the domain expertise of each lecturer. Staff in the Department of Computer Science have built an excellent national and international record in the application of AI and Machine Learning research in sectors ranging from renewable energy to life science. Research funding has been provided by Science Foundation Ireland, Enterprise Ireland, Irish Research Council, Health Research Board, and the European Commission.


Computer Science



PDF Brochure >>


Course Fee

The following is the expected fees schedule for a typical student who begins the programme in September 2018.


  • Full-time Mode of Study: EU Students: €6,500
  • Non-EU Students: Please click here for information


Union of Students in Ireland (USI) Levy

The USI membership levy of €7.00 has been introduced as a result of a referendum where students opted to affiliate to the national Students’ Union. This levy must be paid before the start of Semester 1.


Course duration

  • Full-time: 1 academic year (2 semesters, September to June)
  • No. of weeks per semester: 13
  • No. of timetable hours/week: 18
  • Which days: Monday – Friday


Location: Bishopstown Campus


ECTS Credits: 60


Award: Master of Science in Information Security (Level 9 on the National Framework of Qualifications).



Further Information >>




All modules are worth 5 credits (ECTS) unless otherwise noted.


Semester 1 (Autumn)



Practical Machine Learning Mandatory 5
Knowledge Representation Mandatory 5
Metaheuristic Optimisation Mandatory 5
Big Data Processing Mandatory 5
Research Practice & Ethics Mandatory 5
Natural Language Processing Elective 5
Recommender Systems Elective 5
AI for Sustainability Elective 5
Computer Simulation & Analysis Elective 5
Free Choice Module Elective 5




Semester 2 (Spring)



Deep Learning Mandatory 5
Decision Analytics Mandatory 5
Research Project Mandatory


Robotics & Autonomous Systems Elective 5
Planning and Scheduling Elective 5
Fraud and Anomaly Detection Elective 5
Free Choice Module Elective 5




Module Details >>




  • Please note that applicants will be required to pay an acceptance fee of €500 online if a place on a course is offered. This fee is deductible from the overall course fee.
  • Please attach and upload any documents such as transcripts, CV, other details relevant to the application.
  • Delivery of this programme is subject to sufficient number of applicants. Eligible candidates will be considered on a first come first served basis.


Class Delivery:


Apply Online >>






Online Delivery:


Apply Online >>





Dr Ted Scully
+353 21 4336140