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Course Description

The new MSc 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, Graphics and Vision Technologies and Future Networked Systems.

The course is designed and taught by staff who are renowned research leaders in their fields. The course content is inspired by their cutting-edge work as well as their contacts with leading industry researchers around the globe.

In the first semester, students gain the necessary skills in 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 their specialist modules in their chosen strand.

During the 2nd semester, students will begin foundational work on their dissertation, and immerse themselves in modules of their chosen strand.

The 3rd semester will be exclusively focused on the Dissertations, doing experimental work, building prototypes and writing up the work.

We expect our graduates to be in high-demand for top-end research and development positions within leading multi-national companies and from startup-companies alike. There will also be opportunities to progress to PhD study with many funded positions available locally.

Data Science

Data Science or Big Data has become a hugely important topic in recent years finding applications in Healthcare, Finance, Transportation, Smart Cities and elsewhere. In this strand, Trinity's leading experts in this field will guide you through how to gather and store data (using IoT and cloud computing technologies, process it (using advanced statistics and techniques such as machine learning) and deliver new insights and knowledge from the data.

Data Science Strand Modules:

1st Sem. (Sept-Dec)

Machine Learning
Data Analytics
Research Methods
Scalable Computing

2nd Sem. (Jan-March)

Optimisation Algorithms for Data Analysis
Applied Statistical Modeling
Data Visualisation
Option 1
Security & Privacy
Option 2

3rd Sem. (April-August)


Along with the core modules in the first semester, you will learn the key techniques of Data Mining & Analysis including classification techniques, neural networks and ensemble methods with practical work in the R language. Finally, you will discover how large data sets might be gathered and manipulated in large cloud computing facilities in the Scalable Computing

You will build on this in the 2nd semester with a course on Optimization Algorithms for Data Analysis which will explore topics such as Convex optimization, large dimension simulation with an opportunity to apply your new found skills in a project using Python, R or Scala. In Applied Statistical Modeling, you will deal with many popular techniques such as Markov Chains and Monte Carlo Simulation with an opportunity to apply these techniques to a real data set. You will learn how to reveal the insights derived from large data sets in the Data Visualization module. module and cover essential crypto and security concerns in the Security & Privacy module.

By April, you will have chosen your Dissertation topic, picked and consulted with your chosen supervisor and be ready to develop substantial time researching and prototyping your work. We expect that the top projects should deliver publishable quality papers over this period. At the end of the year, all projects will be showcased to an industry audience comprising indigenous, small & medium employers and multinational companies.

¿En cuál departamento estoy?

Faculty of Engineering, Mathematics and Science

Opciones de estudio

a tiempo completo (1 )

Costos de estudio
€24.669,00 (US$ 30.015) por año
Please refer Trinity College Dublin website for more up-to-date fee details.

*El precio que se muestra es una referencia, por favor verificar con la institución

Fecha de inicio

Septiembre 2021, Enero 2022


Trinity College Dublin, the University of Dublin

College Green,

Dublin 2,


Republic of Ireland

Requerimiento de entrada

Para estudiantes internacionales

For entry to the course, we require the following:

  • A II.1 (60-69%) grade or higher from a reputable university in Computing or strongly related discipline
  • A standard of English language competence that will allow full participation in coursework, classwork and other activities - this means an IELTS level of 6.5. For further details on this please visit the International Students Entry Requirements website
  • You need to be able to be fully competent in programming in C, C++ or Java [for Graphics and Vision Technologies, you will need to have or acquire competence in C++]

All applicants whose first language is not English and who have not been educated through the medium of English must present one of the following qualifications in the English language:

  • IELTS: Grade 6.5 overall
  • TOEFL: 88 internet-based, 570 paper-based, 230 computer-based
  • University of Cambridge: Proficiency Certificate, Grade C or better (CEFR Level C1 or C2), Advanced Certificate, Grade C or better (CEFR Level C1 or C2)
  • Pearson Test of English (Academic) - PTE Academic: a minimum score of 63 to be eligible (with no section score below 59)

Puede haber diferentes requisitos de IELTS en función del curso elegido.


Acerca de Trinity College Dublin

Un hogar lejos de casa para estudiantes que desean convertirse en ciudadanos globales creativos, conscientes y extraordinarios.

  • Escuela de más alto ranking y la más internacional de Irlanda.
  • Campus histórico e inspirador.
  • Destacada lista de egresados y ganadores del Premio Nobel.
  • La mejor universidad europea para emprendedores productores.