School of Computing

MSc in Computing (with Major Options)

Course Code:
DC836 (FT) DC837 (PT)
Course Type:
NFQ Level:
Delivery Modes
Full Time 1 Year; Part Time 2 Years
+353 (0) 1
The University has launched a new student application portal. Link to apply can be found under the 'Introduction' section and the 'Requirements' section

The University has launched a new student application portal. Applications for entry to this course can be made here.  




The MSc in Computing offers a choice of Majors, designed to equip graduates with a range of cutting-edge skills, enabling them to produce high-quality software and systems that deliver solutions to business and the economy.


Major 1 - Artificial Intelligence (This Major is available Full Time Only)

There is a strong demand for graduates with the highly specialised multi-disciplinary skills that are required in AI, both as practitioners in the development of AI applications and as researches into the advanced capabilities required for the creation of next-generation AI systems.  This Major is designed to meet this training need, by providing a balanced programme of instruction across a range of relevant disciplines.


Major 2 - Secure Software Engineering (subject to approval)  (This Major is available both Full Time and Part Time)

In this modern age of increased data usage and ubiquitous computing the security of software is more important than ever. This updated and revised MSc. Major in Secure Software Engineering builds a firm base of advanced software engineering skills and emphasises security from start to finish. It will be appropriate for all those tasked with building and researching secure software systems.


Major 3 - Data Analytics (This Major is available both Full Time and Part Time)

This exciting new Major, delivered in conjunction with leading industry players, builds on the School of Computing's expertise and its involvement with Insight, Science Foundation Ireland's Centre for Data Analytics. Technologies such as the internet, sensor nets, social media and cloud computing are generating vast amounts of data. To say we are drowning in information is an understatement. Yet in this vast sea of raw data, there are gems of knowledge that can be used to improve processes and generate value. This Major provides students with a deep understanding of the issues, techniques and tools to examine large amounts of raw data in order to extract meaningful conclusions from the information these contain.

Major 4 - FinTech & Technology Innovation (This Major is available Part Time only)

The innovation potentiated by the emergence of Financial Technologies (FinTech) holds the prospect of a shift of power over everyday financial transactions away from those who have hitherto held it (in large Financial Organizations) and towards the general population, leading to a potential ‘democratisation’ of finance in areas such as Aggregation, Micro Investing and Crowd-funding. Other key application areas of FinTech Innovation have been towards empowering companies in the Financial Services sector, predominantly in Payment Services and Regulatory Compliance by simplifying and automating their processes.

In this major we draw a distinction between those who actually develop the products which have the potential to empower and those who would use them in a business context. It has been developed to deliver the requisite FinTech background knowledge in key underpinning areas such as Data Governance and Financial Time Series as well as technologies necessary in developing Innovative FinTech technologies e.g. AI and Blockchain.



Please Note:    Part time lectures are scheduled between 4-7pm two evenings a week  

The strong practical focus of the programme culminates in a project, carried out over the summer months. Typically, students will develop a prototype software system in their Major area that targets a real-world problem. They may also analyse processes or techniques, and propose and evaluate alternatives. Most projects are individual but, exceptionally, may be carried out as part of a team.

Students may also be sponsored by external clients or develop their own ideas. Typically, projects commence with a feasibility study, followed by the creation of a project plan and development of a software application or rigorous theoretical analysis.

Over the duration of the programme, students will develop employment-enhancing skills across a number of key areas. These include:

  • Enhancement of proven ability to engineer software
  • Improvement of knowledge of operating systems and networks
  • Development of strong, team-based skills, developed through significant project work during the course
  • Enhanced communication skills through scheduled presentations to lecturers and peers
  • Improved understanding of the business and social context of their work and awareness of new directions
  • Development of research skills to enable contribution of novel ideas, methods and tools to new challenges in their professional careers.

Major 1 - Artificial Intelligence (This Major is available Full Time Only)

- Research Methods & Professional Skills 

- Foundations of Artificial Intelligence               

- Data Analytics and Data Mining                       

- Machine Learning                                                

- Topics in Artificial Intelligence                          

- Data Management and Visualization               

- Statistical Machine Translation                         

- Mechanics of Search                                           

(all of the above are 7.5 ECTS each)

- AI Practicum  30 ECTS




Major 2 - Secure Software Engineering (subject to approval)  (This Major is available both Full Time and Part Time)

- Professional & Research Practice

- System Software

- Secure Programming

- Cloud Technologies

- Formal Programming

- Concurrent Programming

- Software Process Quality

- Network Security

(all of the above are 7.5 ECTS each)

 - AI Practicum 30 ECTS


Major 3 - Data Analytics (This Major is available both Full Time and Part Time)

- Professional & Research Practice

- Statistical Data Analysis

- Cloud Technologies

- Data Management and Visualisation

- Mathematical Methods/Computational Science

- Concurrent Programming

- Data Analytics and Data Mining

- Machine Learning

(all of the above are 7.5 ECTS each)

- AI Practicum 30 ECTS


Please Note:  Part time lectures are scheduled between 4-7pm two evenings a week

Fees Reduction

Flexibile choice of part-time and full-time study and several major options to choose from.

Modern: This course is kept continually up-to-date to reflect changing trends within the computing sector.

Relevant: Acquire knowledge and skills that are in high demand in industry.

The most up-to-date information on fees is available on this website.

The MSc in Computing (with Major), MCM, aims to help meet the demand from industry for recruitment of personnel with significant exposure to relevant, advanced topics in computing. The MCM Programme is suitable for both experienced professionals and recent graduates. It enables software professionals with a number of years' experience to improve proficiency across a range of key disciplines in the field and to update skills beyond the narrow remit of training courses.

It also supports recent graduates of computing and cognate disciplines to gain specialised knowledge and skills for higher-level industry entry at an early stage in their careers.


General Entry Requirements
  • For entry onto this programme, candidates must hold, a second class honours degree or higher in Computer Science, Computing or Computer Applications.
  • International candidates who are non-native speakers of English must satisfy the University of their competancy in the English language.  More information about DCU's English language requirements can be found here.



Next Steps

Make an Application

To apply for this programme:

  • All applicants should apply through  Here's a quick step by step guide if you need help with your application.
  • Please submit certified academic transcripts for all years of study at college or university in original language*, with certified English translations
  • In not more than 500 words, provide a description of your programming language and project experience. 
  • If applicable, evidence of competence in the English language as per DCU entry requirements.  Please see link

* Where an applicant is in their final year of their undergraduate degree, please submit certified transcripts for all years completed to date.

Please note if you are a non EU student and require a study visa, you are not eligible to apply for part-time programmes as study visas are only granted for full-time programmes.

Application Deadlines

Applications will be accepted on a rolling basis until the programme is full or until the following dates: 

  • Closing date for non-EU applicants is 16th July 2021.
  • Closing date for EU applicants is 15th August 2021.

Note applicants who require a study visa for the purposes of studying at DCU, are advised to apply as early as possible.



Commencement of Programme

The programme commences in September 2021.