Program Overview

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Master of Science in Data Analytics

Overview

The Master of Science in Data Analytics is a postgraduate program designed to address the growing need for skilled professionals in data analytics and data-informed decision making. The program enables students with diverse disciplinary backgrounds to develop the necessary technical, communication, research, and organizational skills to be effective in the application of data analytics in real-world contexts.

Program Details

TU Code

TU422

NFQ Level

Level 9

Award Type

Major

Award

Master of Science

ECTS Credits

90

Duration

1 Year

Course Type

Postgraduate

Mode of Study

Full Time

Method of Delivery

On-Campus

Commencement Date

September 2025

Location

Grangegorman

Fees

€8,500 Total Fee (EU), €21,750 Total Fee (Non-EU)

What is Data Analytics?

Data analytics is the extraction of actionable insights from data. It involves the collection, processing, cleaning, and transformation of data followed by the search for patterns in the data. These patterns are visualized and presented in such a way that they can offer critical business insight from the data to practitioners who can then use the insights to improve business, organizational, or social performance.

Program Objectives

The MSc Data Analytics program aims to provide students with the necessary technical skills, communication skills, research skills, and organizational knowledge required to be effective in the application of data analytics in real-world contexts.

Minimum Entry Requirements

• Students without a background in Computing can pursue the MSc Data Analytics as a conversion program. To do so, applicants must have an honors degree at the level of Upper Second Class Honours (2.1) in the area of Science, Engineering, Business, or another subject area provided the student is able to demonstrate appropriate numeracy skills.
• Students with a background in Computing can pursue the MSc Data Analytics as an advanced technical program. To do so, applicants must have an honors degree at the level of Upper Second Class Honours (2.1) in the area of Computing or a related disciplinary area.
• Students with an honors degree at the level of Lower Second Class Honours (2.2) with appropriate work experience may be considered for admission to the program.
• Other applicants who do not meet these accredited learning criteria but who have substantial experience in the relevant field may be considered through a Recognition of Prior Learning process, in line with University policy.

English Language Proficiency

Applicants must have English language proficiency at the level of IELTS (Academic Version) English 6.5 overall (or equivalent) with nothing less than 6 in each component.

Course Content

All students will complete the following modules:

• Fundamentals of Analytics
• Statistics for Analytics
• Data Mining
• Organisational Decision Making
• Data Analytics Research Project Preparation 1
• Data Analytics Research Project Preparation 2
• Data Analytics Research Project

Students following a conversion pathway (i.e., students without a Computing background) take the following modules:

• Programming for Analytics
• Data Exploration

Students from a Computing background take the following modules:

• Advanced Analytics Programming
• Machine Learning

All students will take an elective module such as:

• Programming for Big Data
• Deep Learning
• Digital Ethics
• Machine Learning

Schedule

Teaching takes place from Monday to Friday. As a twelve-month program, classes will commence in early September with the program running until the end of August. Classes take place weekly throughout the semester and in blocks between semesters. Students will finish their Data Analytics Research Project over the summer period.