NCI Course Details

This programme seeks to produce graduates who are able to provide insight, gain value and discover knowledge (at an organisational, societal, or personal level) from data through exercising the skills that are developed through the programmes.

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

• Develop statistical skills to carry out effective data analyses using descriptive and inferential statistics within a business context.
• 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.

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 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.

2021 Graduates used the course to upskill or gain employment in roles such as Collection & Payable Analyst, Data Analyst, Business Process & Data Analyst, Junior Data Specialist, Scalability Analyst, OSM Planner, Trading Analyst, Market Specialist, Business Analyst.

Companies who hired from 2022 graduates of the Higher Diploma in Data Analytics include: Central Bank of Ireland (Statistics Analyst), Intel (Optimization Engineer), Commission for Communications Regulation (Business Analyst), Netscout (Principal Service Engineer), Pfizer (Data Scientist),Coinbase (Compliance Analyst), TikTok (Quality Analyst), Global Shares (Business Reporting Analyst), Citi (Digital Client Support), Enterprise Ireland (Senior Technologist), VHI (Data Analyst), Pinergy (Data Analyst).

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

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. Visit our English Language Requirements page for further information.

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 requirements may be considered based on extensive relevant work and other experience. This may be assessed through a portfolio of learning, demonstration of work produced, interview and assessment (e.g. logic test).

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.

The 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 progress to a major award at level 9 such as the Masters of Science in Data Analytics.

Course Modules 

• Statistics I
• Programming for Data Analytics
• Data Governance
• Statistics II
• Databases for Analytics
• Business Intelligence
• Machine Learning
• Project 

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

The course will be assessed with a blend of continuous assessments and/or project work and exams. This varies between modules but typically assessment is split 60:40 between exams and continuous assessment.

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

Full-time Schedule

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

Part-time Schedule

Blended - Livestream with some on-campus stream classes, scheduled in advance.

Full-Time Option

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

Part-Time Option

Three evenings per week, 18.00 - 22.00. 

Please note that exams can be scheduled during the morning, afternoon or evening Monday to Saturday.

Full-Time Option

3 semesters delivered over 1 year 

Part-Time Option

3 semesters delivered over 1 year 

This course costs €4,900 (fees revised annually) for both Full-time and Part-time deliveries. You can spread the cost of this course with a direct debit plan.