NCI Course Details

The course structure accommodates a wide audience of learners whose specific interests in data analytics may be either technically focused or business focused.

The course will be delivered using academic research, industry defined practical problems, and case studies. This approach will naturally foster a deeper knowledge of the subject area and create transferable skills for work such as critical thinking, problem solving, creative thinking, communication, teamwork, and research skills. The course is completely delivered by faculty and industry practitioners with proven expertise in data analytics.

Upon completion of this course, graduates will be able to:

• Conduct substantial and extensive independent research and analysis in the field of Data Analytics.
• Formulate and implement a novel research idea using the latest industry practices.
• Demonstrate expert knowledge and a critical understanding of data analysis, statistics, and the tools, techniques and technologies of Data Analytics utilised in both technical and business contexts.
• Critically assess, evaluate and communicate business & technical strategies for Data Analytics.
• Formulate, design, assess, and implement effective business & technical solutions for Data Analytics.
• Critically assess and evaluate security, privacy, sustainability, and ethical issues associated with the storage, transfer, and processing of data for analytical purposes.

This course is ideal for graduates that are looking to progress into the emerging data analytics market to increase their employment potential. The course is suitable for graduates who have technical or mathematical problem-solving skills.

Graduates from disciplines that have not developed these skills will need to be able to demonstrate an aptitude for technical or mathematical problem solving.

Core Modules

• Statistics and Optimisation
• Data Mining and Machine Learning
• Analytics Programming and Data Visualisation
• Data Governance, Ethics and Sustainability
• Deep Learning and Generative AI

Research Elective

• Research Practicum OR
• Internship

In addition, there is a choice of two further electives from a set of three elective modules.

Elective Choices

• Data Intensive Scalable Systems
• Modelling and Simulation
• Domain Applications

For the MSc in Data Analytics running in full-time delivery over three semesters, learners choose one of the 6 ECTS elective modules in semester 2, and one of the remaining two ECTS elective modules in semester 3. For the MSc in Data Analytics running in part-time delivery over four semesters, learners choose two of the three ECTS elective modules in semester 3. Electives will be chosen in advance of the semester starting.

Elective modules are subject to availability and a minimum number of students required to run a module.

Assessment

The course will be assessed with a blend of project work and exams. This varies between modules but typically assessment is 50% continuous assessment and 50% exam.

For information on the modules taught on this course view our module descriptors.

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.

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.

Graduates 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-English speaking applicants must demonstrate fluency in the English language as demonstrated by an IELTS academic score of at least 6.0 or equivalent. Visit our English Language Requirements page for further information.

For international students, please visit NCI's Your Country section to view the specific entry requirements for your region.

National College of Ireland has implemented a Bring Your Own Device policy for all courses. Specifically, students are expected to successfully participate in lectures, laboratories and projects using a portable computer (laptop/notebook) with a substantial hardware configuration.

The recommended configuration is as follows:

Processor:

• Intel 11th Gen or newer, Core i3 / i5 /i7 or Ultra 3 / 5 /7
  Or
• AMD 5000 Series or newer, Rzyen 3 / 5 /7

Random Access Memory (RAM):
16GB or greater

Storage:
SSD (Solid State Drive) 256GB or greater

Wireless Card:
802.11 n/ac/ax capability

Recommended Operating Systems:
Windows 11
Later Version of MAC OS should also be fine.
Chromebook’s are not recommended.

It is the responsibility of the student to ensure their computer is functioning correctly and that they have full administrator rights. NCI cannot provide support for these personal devices.

Student Laptop Loan Scheme

A Laptop Loan Scheme is available for eligible students to assist them in completing their chosen course.

Students need to be available 09.00-18.00 Mon – Fri (class days and times vary).

Please note that in some instances exams may take place in the daytime, evening, and/or at weekends.

Campus – Classes will take place face-to-face on campus.

See the MSc in Data Analytics course brochure for an explanation of the learning methods.

1 year; 3 semesters with a practicum or internship.

€7,000 total fee

(EU/Ireland applicants, fees revised annually)

You can spread the cost of this course with a direct debit plan.

NCI Scholarships

We offer a range of scholarships and discounts for both NCI and non-NCI graduates. Current NCI students and alumni can avail of a 25% discount on this course by applying for our Master's Edge Scholarship.

View our full list of scholarships.

The course fee for international students is €17,000.

Fees will be revised annually.

For more information on international fees, please visit International Fees & Funding and International Scholarships.

Learn more about studying at NCI as an international student.