MSc in Computing (with Major Options)

Program Overview

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MSc in Computing (with Major Options)

Course Details

Course Code:

DC836

Course Type:

Postgraduate

NFQ Level:

• Please see for further information

Delivery Modes:

• Full-Time
• Part-Time

Duration:

• FT-1 Year, PT-2 Years

Overview

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.

Natural Language Processing (Full Time Only)

Natural Language Processing (NLP) combines computer science, linguistics and artificial intelligence. The aim of NLP is to develop computer programs with the ability to understand and produce text, as demonstrated in recent chatbots like ChatGPT, LaMDA, and BARD. NLP is an exciting field, because it has the potential to transform the way we interact with machines and each other, and to make our lives easier and more efficient. In cutting-edge research, large language models like the one at the heart of ChatGPT are even beginning to be used for increasingly general AI system development.

Natural Language Processing specialists are in high demand. They are needed to develop and improve technologies such as text classifiers, chatbots, virtual assistants, and language translation systems, which are used by many industries, including e-commerce, healthcare, finance, and more. With the increasing amount of data being generated, the ability to process and understand human language has become crucial for many businesses to make informed decisions. As a result, there is a shortage of skilled NLP professionals, and companies pay highly competitive salaries to attract talent in this field.

This is the first Natural Language Processing master’s degree in Ireland. It has been developed by world-leading academics working in NLP, and is taught by a team of experts from a diverse range of computer science backgrounds including natural language processing, data science, artificial intelligence, and machine learning. An expert panel of industry NLP professionals will deliver a series of guest lectures and engage in practicum supervision. Taught intensively over nine months and building on your background in computer science, this master’s will equip you with the skills you need for a successful career in this fast-growing field.

Data Analytics (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 and ADAPT, the centre for new Human Centric AI techniques. 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 amount 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.

Artificial Intelligence (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 researchers into the advanced capabilities required for the creation of next-generation AI systems. This Major is designed to meet this educational need, by providing a balanced programme of instruction across a range of relevant areas.

Secure Software Engineering (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.

Careers & Further Options

Careers

The MSc in Computing aims to help meet the demand from industry for recruitment of personnel with significant exposure to relevant, advanced topics in computing. This 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.

The focused nature of the majors on our MSc in Computing will ensure that you are in a pole position to gain employment in a wide range of jobs in Ireland and overseas. Graduates of this course have gained employment as a:

• Software Engineer
• Computer Programmer
• IT Project Analyst
• Performance Engineer
• Python/Java Developer
• Web Applications Developer
• Business Analyst
• Technical Analyst
• Technical Consultant
• Data Analyst

Our graduates have gone on to successful careers in leading companies including Google, Facebook, Hubspot, Intel, Apple, Amazon, Microsoft and much more.

Others have progressed to PhD research and gained further advancement and recognition.

Entry Requirements

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 competency in the English language. More information about DCU's English language requirements can be found here.
• Recognition of Prior Learning (RPL) applicants are required to submit a cover letter along with their application under the Transcripts section of the portal, affirming their intent to apply for RPL. For more information on RPL see here.

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.

Programme Structure

About this course

The strong practical focus of the programme culminates in a project practicum, 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.

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

Natural Language Processing

• Foundations of Natural Language Processing
• Introduction to Machine Learning
• Professional & Research Practice
• Human Factors in NLP
• Deep Learning for Natural Language Processing
• Advanced Machine Learning
• Data Analytics & Data Mining
• Machine Translation (Elective)
• Mathematical Methods/Computational Science (Elective)

(all of the above are 7.5 ECTS each)

• NLP Practicum (30 ECTS)

Data Analytics

• Professional & Research Practice
• Statistical Data Analysis
• Cloud Technologies
• Data Management and Visualisation
• Mathematical Methods/Computational Science
• Artificial Intelligence, Information and Information Seeking
• Data Analytics and Data Mining
• Machine Learning

(all of the above are 7.5 ECTS each)

• DA Practicum (30 ECTS)

Artificial Intelligence

• Professional and Research Practice
• Foundations of Artificial Intelligence
• Statistical Data Analysis
• Data Analytics and Data Mining
• Machine Learning
• Artificial Intelligence, Information and Information Seeking
• Data Management and Visualization
• Statistical Machine Translation (Elective)
• Mechanics of Search (Elective)

(all of the above are 7.5 ECTS each)

• AI Practicum (30 ECTS)

Secure Software Engineering

• Professional & Research Practice
• System Software
• Secure Programming
• Cryptography and Number Theory
• Formal Programming
• Concurrent Programming
• Software Process Quality
• Network Security

(all of the above are 7.5 ECTS each)

• SSE Practicum (30 ECTS)

Fees and Funding

Fees

Faculty of Engineering & Computing International Scholarship

This scholarship is available for Non-EU applicants who have received an offer to study on eligible postgraduate programmes in the Faculty of Engineering and Computing. Successful recipients will receive a €5,900 fee reduction on the full-time 2025–2026 Non-EU Tuition fee.

• Full time
  • EU Status Fee: €7,700
  • Non EU Fee: €25,000
• Part time
  • EU Status Fee Part-time: See Modular Fees

How To Apply

To apply for this programme:

All applicants should apply here.

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

Programming Language Experience - Please upload a statement about your experience with a programming language. You should provide an example of an occasion when you wrote a piece of code, how you approached the task and what the code delivered. Please also include a sample of your own code.

• If applicable, evidence of competence in the English language as per DCU entry requirements. Please see link

Application Deadlines

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

• EU Applications are open until 30th August 2025.
• Non EU Applications are now closed for this programme. It is advised to apply for an alternative programme.

Application Queries

• For EU applicant queries, please visit postgraduate-taught-admissions or email
• For non EU applicant queries, please visit

postgraduate or email

Commencement of Programme

The programme commences in September 2025.

Program Outline

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Degree Overview:

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Objectives:

This Master of Science (MSc) program in Computing provides graduates with cutting-edge skills to develop high-quality software and systems, addressing business and economic needs. Graduates can pursue either a career path in industry or research and development in academia or the private sector.

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Description:

• This MSc in Computing program offers five Major options:
• Natural Language Processing (NLP)
(Full-time only): focuses on developing software for understanding and generating text, with applications in chatbots, virtual assistants, and language translation.
• Data Analytics (DA)
(Full-time and Part-time): delves into analyzing large data sets to extract meaningful conclusions and improve decision-making processes in various industries.
• Artificial Intelligence (AI)
(Full-time only): provides in-depth knowledge of AI principles and techniques for building next-generation AI systems with potential applications in diverse fields.
• Secure Software Engineering (SSE)
(Full-time and Part-time): emphasizes building secure software throughout the development lifecycle, crucial in the modern era of digital security concerns.
• FinTech & Technology and Innovation (FT)
(Part-time only): explores the use of technologies like AI and Blockchain to revolutionize financial services and empower individuals with more control over their finances.
• The program combines theoretical foundations with practical application through projects.
Students choose an area in their Major for which they design and develop a prototype software system addressing a real-world problem.
• Students develop key employability skills for their chosen career path, including software engineering skills, project management, communication, teamwork, problem-solving, research skills, and awareness of social and ethical considerations in their field.
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Outline:

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Structure:

• Part-time students attend lectures two evenings per week.
• The program culminates in a project practicum, conducted during the summer months, where students typically develop a prototype software system in their chosen Major that addresses a real-world problem.

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Content:

• Each Major features specific modules focusing on relevant methodologies, technologies, and applications within that specific field:
• NLP Major:
• Foundations of Natural Language Processing
• Introduction to Machine Learning
• Human Factors in NLP
• Deep Learning for Natural Language Processing
• Advanced Machine Learning
• Data Analytics & Data Mining
• Machine Translation
• Mathematical Methods/Computational Science
• NLP Practicum (30 ECTS)
• DA Major:
• Statistical Data Analysis
• Cloud Technologies
• Data Management and Visualisation
• Mathematical Methods/Computational Science
• Artificial Intelligence, Information and Information Seeking
• Data Analytics and Data Mining
• Machine Learning
• DA Practicum (30 ECTS)
• AI Major:
• Foundations of Artificial Intelligence
• Statistical Data Analysis
• Artificial Intelligence, Information and Information Seeking
• Data Management and Visualization
• Statistical Machine Translation
• Mechanics of Search
• AI Practicum (30 ECTS)
• SSE Major:
• System Software
• Secure Programming
• Cryptography and Number Theory
• Formal Programming
• Concurrent Programming
• Software Process Quality
• Network Security
• SSE Practicum (30 ECTS)
• FT Major:
• FinTech - Financial Innovation (5 ECTS)
• Blockchain: Basics and Applications (7.5 ECTS)
• Statistical Data Analysis (7.5 ECTS)
• Machine Learning (7.5 ECTS)
• High Tech Innovation & Entrepreneurship for FinTech (7.5 ECTS)
• FinTech Practicum (30 ECTS)
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Assessment:

• Assessment methods vary depending on the Major and specific module content but typically include a combination of:
• Continuous assessment
• Examinations
• Project work (including presentations)
• Portfolio submissions

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Assessment criteria for all Majors include demonstration of:

• In-depth knowledge and understanding of relevant concepts
• Ability to apply theoretical concepts and implement practical solutions
• Strong analytical and problem-solving skills
• Effective communication (both written and oral)
• Teamwork skills and ability to contribute productively within a group
• Research skills (for project work and thesis, if relevant)
• Professionalism and ethical awareness
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Teaching:

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Methods:

• Teaching methods are tailored to each specific module and may include:
• Lectures and seminars (for theoretical foundations and knowledge building)
• Practical workshops and tutorials (for hands-on skill development)
• Project work (for applying knowledge, developing problem-solving skills, and fostering teamwork)
• Guest lectures from industry professionals (bringing real-world experiences and insights into the classroom)

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Faculty:

• The program is delivered by highly experienced and qualified faculty drawn from Dublin City University's School of Computing, featuring experts in each specific Major:
• NLP:
• World-leading academics in NLP with extensive research experience and involvement in relevant research centers like Insight and ADAPT.
• DA:
• Experts in data science, data analysis, and related technologies, with expertise in various industry applications and research fields.
• AI:
• Multi-disciplinary faculty with specialized expertise in AI theory, algorithms, design, development, and applications across diverse areas.
• SSE:
• Faculty with strong research and industry experience in secure software development, programming languages, cryptography, formal methods, concurrency, network security, and related fields.
• FT:
• Faculty with combined expertise in finance, technology innovation, FinTech applications, blockchain technology, data analysis, machine learning, and entrepreneurship.

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Unique Approaches:

• Strong emphasis on practical, project-based learning through individual and team projects, fostering application of theory and development of employable skills.
• Close industry involvement through guest lectures, project collaborations, and internship opportunities, ensuring program content remains relevant to current industry demands and prepares graduates for real-world applications.
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Careers:

• The MSc in Computing program prepares graduates for diverse career opportunities across various sectors:

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Specific Careers per Major:

• NLP:
• Natural Language Processing Specialists
• Machine Learning Engineers
• Data Scientists
• Software Developers (focused on NLP-based applications)
• Research Scientists (NLP)
• DA:
• Data Analysts
• Business Intelligence Analysts
• Data Scientists
• Machine Learning Engineers
• Cloud and Big Data Engineers
• AI:
• AI Developers
• Machine Learning Engineers
• Robotics Engineers
• Computer Vision Specialists
• Research Scientists (AI)
• SSE:
• Secure Software Developers
• Security Architects
• Cryptographic Engineers
• Penetration Testers
• Software Quality Assurance Specialists
• FT:
• FinTech Developers
• Blockchain Developers
• Financial Data Analysts
• FinTech Entrepreneurs
• Investment and Trading Analysts

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General Career Opportunities for all Majors:

• Consultancy
• Management
• Leadership Positions
• Research and Development
• PhD studies
• Academic Careers

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Industry sectors employing graduates:

• Technology companies
• Financial service providers
• Consulting firms
• Research institutions
• Government agencies
• Healthcare
• Manufacturing
• Retail
• Education
• Many more
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Other:

• The School of Computing offers excellent teaching and research facilities, including modern laboratories, computer suites, and high-tech learning spaces.
• Graduates have consistently high employment rates, with many securing positions in leading national and multinational companies.
• The program provides an excellent foundation for further research in a PhD program for those interested in pursuing an academic or research-focused career.

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Tuition Fees and Payment Information:

Full time EU Status Fee €7,500 Non EU Fee. €25,000 Part time EU Status Fee Part-time See Modular Fees