Master in Computer Science (Data Analytics)

Course details

Almost everything we do results in data being created and stored somewhere. Individuals, communities, business and governments face major challenges in harnessing all this data to create knowledge that that will underpin a healthier, safer, more productive world.

• Organizations worldwide are facing a rapid growth in volume, velocity and complexity of data
• Computational analytics of large and heterogeneous volumes of data requires new approaches and tools
• This is exacerbated by the global shortage of data analytics talent, particularly of Individuals with the required deep technical knowledge and analytical skills

This is an advanced MSc programme that provides graduates of Computer Science and closely related areas with in-depth knowledge and skills in the emerging growth area of Data Analytics. It includes topics such as large-scale data analytics, information retrieval, data mining, natural language processing, and web data analytics. It also includes foundational modules in topics such as statistics and programming for data analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner.

Key facts

Entry requirements

This MSc is suitable for high-performing graduates of Computer Science and closely related degree programmes. Entry to the programme is open to Individuals who have at least an upper second class honours (2.1) in a Level 8 degree in either the BSc in Computer Science and Information Technology or the BE in Electronic & Computer Engineering in NUI Galway, or another degree programme that is similar in content and level and is from a recognised university or third level college.

Course outline

This is a 90-ECTS course with three main elements: foundational modules (20 ECTS), advanced modules (40 ECTS), and a substantial capstone project (30 ECTS).

Foundational modules include: Statistics & Probability;Programming for Data Analytics; Digital Signal Processing; and Research Fundamentals.

Advanced modules include: Large Scale Data Analytics; Web-Mining; Information Retrieval; Machine Learning & Data Mining; System Modelling & Simulation; Embedded Signal Analysis; Natural Language Processing; and Data Visualisation.

Students work on their Individuals projects during the full year, building on the knowledge they acquire during the course, and submit them in August. Projects may have a research or applied focus. Note that the modules offered may change in response to changes in industry and research demands.

Further education

• This is a distinctive programme that is closely aligned to the research and teaching expertise of the Information Technology discipline and the Insight Centre for Data Analytics in NUI Galway.
• It will opens the door for graduates to new career opportunities in industry, in starting new ventures or in PhD-level research.

Requirements and assessment

Semester 1 exams: December. Semester 2 exams: April/May. Assessment is based on a combination of assignments and written exams. The final project is submitted in August and assessed through a combination of a written thesis, an oral examination and a demonstration.