Higher Diploma in Science in Data Analytics

Higher Diploma in Science in Data Analytics – NFQ Level 8

Start Date: 7th September 2026
Duration: 1 Academic Year
Learning Mode: On Campus
ECTS Credits: 60

The Higher Diploma in Science in Data Analytics is a one-year, 60-credit programme awarded at NFQ Level 8. This programme is designed for graduates who want to build specialist knowledge and practical skills in one of today’s fastest-growing and most in-demand industries.

Learners will develop expertise in data analysis, statistics, programming, machine learning, business intelligence, and data visualisation. Through practical and industry-focused learning, students will gain the skills required to analyse complex datasets, generate actionable insights, and support strategic decision-making across a wide range of sectors.

The programme combines theoretical understanding with applied technical skills, preparing graduates for professional employment in data analytics and related technology roles.

Learning Mode

On Campus
Delivered from our Dublin 2 campus through classroom-based lectures and practical lab sessions.

Typically delivered over 3 full days per week between 9am and 5pm across two semesters.

Qualifications

Upon successful completion of the programme, learners will achieve:

• Higher Diploma in Science in Data Analytics – NFQ Level 8

Entry Requirements

Applicants should hold:

• A Primary Honours Degree (NFQ Level 8) in a non-cognate discipline from a recognised institution or equivalent qualification

Applicants with strong technical, mathematical, or problem-solving skills may be prioritised during selection.

Recognition of Prior Learning (RPL) applications are considered on a case-by-case basis.

International applicants whose first language is not English must demonstrate English language proficiency equivalent to IELTS 6.0 (B2+ CEFRL) or recognised equivalent.

Course Structure

The programme is delivered full-time over one academic year and combines lectures, workshops, practical exercises, and applied project work.

Learners will build advanced analytical and technical skills through practical use of industry-relevant tools, technologies, and methodologies.

Modules

• Fundamentals of Data Analytics
• Programming in Python
• Statistics for Data Analysis
• Data Mining
• Data Management
• Business Intelligence & Data Warehousing
• Modelling for Data Analytics
• Big Data
• Applied Machine Learning
• Data Visualisation

Programme Objectives

This programme aims to:

• Develop practical and technical data analytics skills for industry
• Build knowledge of statistics, programming, machine learning, and data modelling
• Enable learners to critically evaluate and solve complex data-related problems
• Support progression to further study at NFQ Level 9
• Prepare graduates for professional roles in data analytics and business intelligence
• Develop advanced analytical thinking, data management, and problem-solving skills

Career Opportunities

Graduates may pursue careers such as:

• Data Analyst
• Business Intelligence Analyst
• Data Visualisation Specialist
• Junior Data Scientist
• Reporting Analyst
• Data Engineer Support Roles
• Machine Learning Support Roles

The programme also provides a strong foundation for progression to postgraduate study or professional analytics certifications.

Course Fees

Location: Dublin 2

Fees

• €6,150 – Irish/European Nationals
• €6,150 – Non-EU Nationals Residing in Ireland (Stamp 2)
• €8,600 – Non-EU Applicants Applying from Outside Ireland

All fees are payable per academic year.

Why Choose This Programme?

✔️ NFQ Level 8 qualification in a high-demand industry
✔️ Practical hands-on learning with industry-relevant tools
✔️ Learn Python, Machine Learning, Big Data & Visualisation
✔️ Delivered on campus with expert lecturer support
✔️ Strong pathway into data-focused careers and postgraduate study
✔️ Designed for graduates seeking to upskill or transition into tech

Location & Start Date

Location: On Campus – Dublin 2
Start Date: 7th September 2026
Duration: 1 Academic Year