MSc in Computer ScienceData Science StrandData 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.
Michaelmas Term (Sept-Dec)
Hilary Term (Jan-March)
Summer Term (April-August)
|Machine Learning||Optimisation Algorithms for Data Analysis||Dissertation|
|Data Analytics 1||Data Analytics 2|
|Research Methods and Innovation||Applied Statistical Modelling|
|Scalable Computing||Security & Privacy|
|Data Visualisation||Option 2|
|Option 1||Option 3|
Option 1 and Option 2 are elective modules selected from the other strands.
Along with the core modules in the first semester, you will learn the key techniques of Data
& 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
gathered and manipulated in large cloud computing facilities in the Scalable
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 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 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 indigenous, small & medium employers and multinational companies.