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.

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.

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.

Core Modules

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

Elective Choices

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

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

Research Elective

• Research Practicum OR
• Internship**

**The Internship module is available to students as an elective in their final semester. Please note that in view of the restrictive and specialist nature of the programme, the School of Computing reserves the right not to offer certain modules on an elective basis

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 degree) qualification (2.2 or higher) on the National Framework of Qualifications. Applicants may be from a cognate/STEM background. Standard applicants for the programme are those who hold computing or numerate degrees. 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.

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.

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.

On-campus face-to-face classes.

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

This course runs over 1 year; 3 semesters with a final internship/research practicum

€6,800 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 for September 2024 is €15,000.

From the January 2025 intake onwards, the course fee for international students will be €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.