Program Overview

Overview of the M.Sc. in Computer Science – Intelligent Systems Programme

The M.Sc. in Computer Science – Intelligent Systems programme focuses on smart, interactive web applications and systems, which are becoming an integral part of our daily lives at home, in the workplace, and in social interaction. Designing and building these systems requires expertise in artificial intelligence, human language understanding and generation, web systems and applications, data analytics, and knowledge engineering. This strand is closely linked to the school’s research groups involved in the ADAPT national research centre for Digital Content Technology.

Is This Course For Me?

This course is designed for graduates from a computing or closely related undergraduate background. Candidates with a good undergraduate Honours degree in disciplines such as engineering, mathematics, or statistics are also encouraged to apply, if they have acquired good programming skills. Candidates will be required to provide evidence of their computing skills and experience.

Career Opportunities

Employment opportunities exist in a range of areas such as internet-based services, financial services, mobile communication companies. Students will also benefit from the comprehensive research scope, networks, and wealth of research achievements in both the School and the ADAPT Centre. Graduates will be suited to careers in web technology companies such as Google, Facebook, Twitter, Amazon, LinkedIn, Microsoft, IBM, PayPal, Symantec, eBay, and SAP, Business-Intelligence led organisations, Consultancy companies, Innovative start-ups building intelligent applications, and IT teams within large service organisations.

Course Structure

The full M.Sc. programme, comprising 90 ECTS credits, takes one full calendar year to complete and leads to the qualification of M.Sc. in Computer Science – Intelligent Systems, a Level 9 award under the Irish National Framework for Qualifications (NFQ).

• Between September and April, students attend two 12-week teaching semesters, each followed by an assessment period, where they take a range of taught modules.
• Then, from April to August, students work full-time on their individual research dissertations.

Students may exit with an award of Postgraduate Diploma (P.Grad.Dip.) in Computer Science – Intelligent Systems (NFQ Level 9) upon successful completion of 60 ECTS of taught modules, not including the Research Dissertation.

Course Content

The following core modules are taken by all students on the course:

• Machine Learning
• Artificial Intelligence
• Information Retrieval & Web Search
• Knowledge & Data Engineering
• Adaptive Applications
• Text Analytics
• Advanced Software Engineering
• Research Methods and Innovation

Students also take a number of individually chosen elective modules from a pool of options.

Finally, all students complete a substantial Research Dissertation which comprises a third of the entire course.

Admission Requirements

Applicants must provide the following:

• An upper second-class (2.1) Honours degree grade or higher from a reputable university, in Computing or related discipline.
• All applicants whose first language is not English or who have not been educated through the English language will need to present evidence of competency.
• Proven programming competence. All candidates will have to complete a programming test in C, C++ or Java before being offered a place on the course. Some modules may also require programming in Python and other languages.
• A strong work ethic and the resolve to engage with a demanding but rewarding programme.

English Language Requirements

All applicants to Trinity are required to provide official evidence of proficiency in the English language. Applicants to this course are required to meet Band B (Standard Entry) English language requirements.

Course Fees

For a full list of postgraduate fees, the information is available through the university's official channels.

Awards

• NFQ Level 9
• Number of Places: 30 Places
• Next Intake: September 2025

Course Coordinator and Director

• Course Coordinator: Gaye Stevens
• Course Director: Professor Doug Leith (Course Director) / Dr. John Dingliana (Co-Director for Admissions)

Closing Date

• 31st July 2025

This programme is designed to equip students with the skills and knowledge necessary to thrive in a fast-changing digital world, focusing on intelligent systems that are integral to our daily lives. With its comprehensive curriculum and research opportunities, graduates are well-prepared for careers in a variety of sectors, including web technology, financial services, and consultancy companies. The programme's emphasis on artificial intelligence, data analytics, and knowledge engineering ensures that students are at the forefront of technological advancements, making them highly sought after in the job market.