Date Analytics

The objective of this course is to provide you a broad combination of themes around data analytics that creates valuable insight and professional expertise. The programme has been designed and developed with industry experts to ensure that graduates develop core theoretical and practical skills in specialist areas such as Statistics, Business Intelligence, Data Governance, Databases, Programming and Machine Learning. This course will equip you to enter the world of data and business analytics.



Who is the course for?

This programme is suitable for non-technical professionals and college graduates from non-technical disciplines, those with numeracy skills who wish to work as data analysts, business analysts or to enter into management roles across a range of sectors. You do not need to have previously studied programming. However, given the timeframe and the amount of technical and statistical content, applicants should be prepared to commit fully to the course.

Course Content



• Statistics and Probability

• Programming for Data Analytics

• Governance, Ethics, Security & Sustainability

• Deep Learning and Generative AI

• Databases for Analytics

• Business Intelligence and Visualisation

• Data Mining and Machine Learning

• Cloud and Scalable Analytics

• Project

Applicants holding an honours degree (level 8 or equivalent) in any discipline are eligible for direct access to the programme. In addition, applicants with level 7 degree in a cognate area (e.g. Computer Science/IT, Engineering, Mathematics, Physics, Information Systems, Accounting) are also considered for direct access into the programme.



For other non-standard applications 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.



Typically, holders of more technical and numerate degrees or candidates that are able to demonstrate technical or mathematical problem-solving skills are likely to gain a higher ranking in the selection for the course.



Non-English-speaking applicants must demonstrate fluency in English evidenced by an IELTS academic score of at least 6.0 or equivalent.



Laptop Requirement

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.

Application: Apply online at www.ncirl.ie

Part-time Schedule

Part-Time (1-Year) 3 semesters delivered over 1 calendar year.



Delivery

Blended - Livestream Currently some on campus, fully online pending subject to QQI approval.



Indicative Timetable

Three evenings per week, 18.00 - 22.00.



Full-time Schedule

Full-Time (1-Year) 3 semesters delivered over 1 calendar year.



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 can vary)

Part-time

Start Date Sept 2026



Full-time

Start Date Sept 2026 and Jan 2027

Award and Progression

Higher Diploma in Science in Data Analytics is awarded by QQI at level 8 on the National Framework of Qualifications. Students who successfully complete this course may be eligible to progress to a major award at level 9 on the NFQ.