• A grade of at II.1 (Upper Second Class Honours) or higher from a reputable university, in Computing or a strongly related discipline.
• A standard of English language competency that will allow full participation in coursework, classwork and other activities. Specifically, if English is not your first language, you are required to submit an English competency certificate with a minimum IELTS level of 6.5 or equivalent in order for your application to be considered. For details on alternative English Tests accepted, please visit TCD’s International Students Entry Requirements website.
• You need to be able to be fully competent in programming. All candidates will have to complete a programming test in C, C++ or Java before being offered a place on the course. Some modules on the course may also require programming in Python and other languages.
• A strong work ethic and the resolve to strongly engage with the demanding programme. This means, for example, that it will be extremely difficult to do the course while holding part-time employment. Students should expect to engage in a large amount of practical work during the course.
• Please note that the above are only the minimum requirements for entry. The admissions process is competitive and higher scores may be required to secure a place on the course
Months of entry
The new M.Sc. in Computer Science has a common set of entry criteria and leads to a Master's degree in Computing, specializing in one of four exciting areas: Data Science, Intelligent Systems, Augmented & Virtual Reality and Future Networked Systems. The course is designed and taught by staff who are leading experts in their fields, and the course content is inspired by their cutting-edge work as well as their contacts with leading industry researchers around the globe. We expect our graduates to be in high demand for high-end research and development positions within leading multi-national companies and start-up companies alike. In some cases our graduates have gone on to take up funded PhD studies at TCD.
The Intelligent Systems Strand 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 centre for Digital Content Technology.
The marketplace of the future will see intelligent behaviour becoming the standard for computer systems. The courses within the Intelligent Systems strand will provide graduates with the ability to specialise in intelligent adaptive systems and artificial intelligence, providing them with the necessary skills to become leaders in these fields. Employment opportunities exist in a wide 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.
The course is taught over a full calendar year, with two 12-week semesters of taught modules, involving attendance at labs and lectures, followed by dedicated research work over the remaining summer months for the MSc Dissertation.
In the first term (September - December), all students gain the necessary skills in a number of Core Modules common to the M.Sc. Programme. These include Research Methods (to enable students to produce their own dissertation), Innovation (to equip students with skills in company formation or innovating within a large company) and Machine Learning (a foundational technique for each of the specializations). In addition, students will make a start on specialist modules in their chosen strand. They will gain a grounding in Information Retrieval & Web Search, and examine, in-depth, the theoretical and practical issues involved in searching the web or any or large corpus of documents, including text processing, ranking scores, classification etc. In Knowledge & Data Engineering, they will learn about the semantic web including model design, reasoning and querying. All students take a 10-credit module in Advanced Software Engineering, taught over two terms, which explores the methods and techniques involved in large-scale software development encompassing Agile and eXtreme Programming (XP), Test-driven development and Re-factoring.
During the second term (January – March), students begin foundational work on their dissertation, and immerse themselves in further specialist modules of their chosen strand. The term will deal with Artificial Intelligence techniques, including models of human cognitive architectures, knowledge representation techniques such as Ontologies and models of natural language processing. This module is complemented by the Text Analytics module which demonstrates how finite-state methods, model theory and category theory can be used to analyse content and determine sentiment. The Adaptive Applications module is hands-on, exploring how applications can adapt to suit individual users. In addition, students choose three additional electives (one in Term 1 and two in Term 2) from a pool of modules offered in the other strands of the M.Sc. programme.
The summer term (April – August) will be exclusively focused on the Dissertations, doing experimental work, building prototypes and writing up the work. By April, students will have chosen a Dissertation topic, picked and consulted with their chosen supervisor and be ready to devote substantial time to researching and prototyping your work. We expect that the top projects should deliver publishable quality papers over this period. During the year, all projects will be showcased to an industry audience comprising indigenous, small & medium employers and multinational companies.
Please note that the course content is updated on an annual basis and some changes occur from year to year. Students accepted on the course will be given formal module descriptors before the start of term.
Fees and funding
Qualification, course duration and attendance options
- full time12 months
- Campus-based learningis available for this qualification
- part time24 months
- Campus-based learningis available for this qualification
Course contact details
- Dr. John Dingliana