MSc in Computer Science (Data Analytics)

This is an advanced MSc programme that is delivered full-time over one year, and provides graduates of Computer Science and closely related areas with in-depth knowledge and skills in the emerging growth area of Data Analytics and Data Science. The MSc in Data Analytics is delivered by a team of highly respected academics based in NUI Galway that are considered international experts in their respective fields. Some of the topic areas include large-scale data analytics, advanced data-mining and machine learning, deep learning, information retrieval, natural language processing, data visualisation, web mining, linked-data analytics, simulation and modelling, and digital image processing. 

This programme is aimed at graduates with a primary qualification in Computer Science or related subject area. It is not a conversion course, and students are expected to be already at a very high technical standard with regard to the technical elements of their computing background.

In addition to completing a range of advanced modules, students will then reinforce their newly gained skills through a 30-credit project that is completed during the summer and evaluated through a thesis (minor dissertation) format. For these projects, students work directly with an academic supervisor in their chosen area of specialisation, while they also can pursue the opportunity to collaborate with a research groups across NUI Galway or with an industry partner.

The MSc is a 90-ECTS course with three main elements:-

• Core modules (40 ECTS)
• Optional modules (20 ECTS)
• A substantial capstone thesis project (30 ECTS)

Core modules include:-

• Programming for Data Analytics
• Introduction to Natural Language Processing
• Machine Learning and Data Mining
• Data Visualisation, Deep Learning
• Web and Network Science
• Information Retrieval 
• Case Studies in Data Analytics

Optional modules include:-

• Modules in Statistics and Probability
• Advanced Natural Language Processing
• System Modelling & Simulation
• Embedded Image Processing
• Linked Data Tools
• Techniques for Large Scale Data Analytics

From Semester 2 onward, students work on individual projects and submit them in August. Projects may have a research or applied focus.