Course Summary
The overall goal of the MSc in Data Analytics programme is to provide graduates with essential research and development skills in Data Analytics. It is envisaged that graduates from this programme will be well equipped to perform independent research that enables them to make informed and critical decisions regarding requirements elicitation and analysis, implementation, evaluation, and documentation in Data Analytics.
College Link
Career Sectors
This course prepares you for working in the Career Sectors below. Follow the links to get a fuller understanding of the sectors you are preparing for.
Entry Requirements
A minimum of a level 8 honours qualification (2.2 or higher) or equivalent on the National Qualifications Framework in a cognate discipline. Given the target technical market for graduates of this programme, candidates will be required to demonstrate technical or mathematical problemsolving skills as part of previous programme learning. Standard applicants for the programme are those holders of technical, numerate degrees. Graduate from disciplines which do not have technical or mathematical problem-solving skills embedded in their programme will need to be able to demonstrate technical or mathematical problem-solving skills in addition to their level 8 programme qualifications (Certifications, Additional Qualifications, Certified Experience and Assessment Tests). All applicants for the programme must provide evidence that they have prior programming experience (e.g., via academic transcripts or recognised certification).
For candidates who do not have a level 8 qualification the College operates a Recognition of Prior Experiential Learning (RPEL) scheme meaning applicants who do not meet the normal academic entry requirements, may be considered based on relevant work or other experience. Non-Englishspeaking applicants must demonstrate fluency in the English language as demonstrated by an IELTS academic score of at least 6.0 or equivalent.
Laptop Requirement
This programme has a BYOD (Bring Your Own Device) policy. Specifically, students are expected to successfully participate in lectures, laboratories and projects using a portable computer (laptop/notebook) with a substantial hardware configuration. The minimal suitable configuration is 8GB of RAM (16GB are recommended); a modern 64-bit x86 multicore processor (Intel i5 or superior); 250+ GB of available space in hard disk; WiFi card; and a recent version of Ubuntu, macOS, or Windows.
It is the responsibility of each student to ensure their computer is functioning correctly and that they have full administrator rights. NCI IT cannot provide support for these personal devices.
Some students may be able to avail of the Student Laptop Loan Scheme, subject to eligibility.
Application Details
Application: Apply online at www.ncirl.ie
Part-time
Start Date Sept 2025
Full-time
Start Date Sept 2025 and Jan 2026
Fees
Part-time:
€4,800 per annum. €9,600 total fee. (Fees revised annually).
Full-time:
EU Fee: €7,000 total fee (EU/Ireland applicants). (Fees revised annually).
The Student
Career Interests
This course is typically suited for people with the following Career Interests. If these interests do not describe you, this course may prepare you for work you may not find satisfying.
Investigative
The Investigative person will usually find a particular area of science to be of interest. They are inclined toward intellectual and analytical activities and enjoy observation and theory. They may prefer thought to action, and enjoy the challenge of solving problems with sophiscticated technology. These types prefer mentally stimulating environments and often pay close attention to developments in their chosen field.
Career Progression
The Master of Science in Data Analytics is awarded by QQI at level 9 on the National Framework of Qualifications. Students who successfully complete this course may progress to a major award at level 10 on the NFQ. Students may also elect to exit early with the Postgraduate Diploma in Science in Data Analytics at level 9 on the NFQ.
Duration
2 years; 4 semesters with a research practicum or internship
Delivery: Blended - Livestream with some on-campus stream classes, scheduled in advance.
Indicative Timetable: Two evenings per week, 18.00 - 22.00 and every second Saturday.
Full-time Schedule
1 year; 3 semesters with a practicum or internship
Delivery: Campus – Classes will take place face-to-face on campus.
Indicative Timetable: Students need to be available 09.00-18.00 Mon – Fri. Class days and times vary.