Computer Science - Data Science
1 year full-time
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 focussed 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.
1 year full-time
As a large number of applications for the MSc in Computer Science - Data Science have already been received, regrettably we are currently unable to accept any further applications. However, if places become available applications will be reopened at the end of March/early April.
The MSc programme aims to produce very high quality graduates that can become leaders in high-tech industry and academic research. It will be intensive, demanding and rewarding.
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 futher 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++]
- 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.
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 techiques such as machine learning) and deliver new insights and knowledge from the data.
Data Science Strand Modules:
1st Sem. (Sept-Dec)
2nd Sem. (Jan-March)
Optimisation Algorithms for Data Analysis
Applied Statistical Modelling
Security & Privacy
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 Optimisation Algorithms for Data Analysis which will explore topics such as Convex optimisation, large dimension simulation with an opportunity to apply your new found skills in a project using Python, R or Scala. In Applied Statistical Modelling, you will deal with many popular techniques such as Markov Chains and Monte Carlo Simulation with an opportuniuty 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 Visualisation module. module and cover essential cyrpto and security concerns in the Security & Privacy module. In addition, you can choose two additional modules from a pool.
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 indiginous, small & medium employers and multinational companies.
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Prof. Séamus Lawless