Entry Points (2018)

Course Overview

Are you good at maths, interested in coding, and keen to study people as well as equations? Do you like the idea of using data to understand the human condition? If so, the new BA in Arts with Data Science may be for you.

Data science is the art of extracting useful knowledge from raw data, and then communicating that knowledge to others. Data scientists need strong quantitative and coding skills, but they are not narrow technical specialists. For example, to learn from psychological data, you need to have a good understanding of psychology.

In this unique four-year programme, you will build an outstanding portfolio of data science skills, while simultaneously studying a relevant Arts discipline (Psychology, Economics, Geography, History or Philosophy) to Joint Honours level. You will graduate with a proven track-record of applying data analytics techniques to real-world human problems. Few skills are more highly valued by employers.


Applications and Selections

Who Teaches this Course

Requirements and Assessment

Key Facts

Entry Requirements

Minimum Grade H5 in two subjects and passes in four other subjects at O6/H7 Grades in the Leaving Certificate, including Irish, English, another language and three other subjects recognised for entry purposes. A H5 or O1 Grade in Leaving Certificate Mathematics is also a requirement.

Additional Requirements


4 years

Next start date

Sept 2019

A Level Grades (2018)


Average intake


Closing Date

NFQ level

Mode of study

ECTS weighting




Course code

Course Outline

Students study Data Science and Mathematics for Data Science choose one of the following Arts major subjects: Psychology, Economics, Geography, Philosophy or History. 

Arts major+
• Skills for Data Science 1
• Programming 1
• Programming 2
• Probability 1
• Statistics
• Analysis and Algebra 1
• Analysis and Algebra 2
• Skills for Mathematics

Arts major+
• Skills for Data Science 2
• Database Systems
• Probability 2
• Statistical Inference
• Linear Algebra

Data Science Accelerator in Semester 1:
• Skills for Data Science 3
•Philosophy of Statistics and Machine Learning
• Artificial Intelligence
• Calculus
• Formal Logic or Discrete Mathematics

Work placement in Semester 2.

• Arts major + Machine Learning
and Text Mining
• Applied Regression Models
• Stochastic Processes or Statistical Modelling
• Data Science project

Curriculum Information

Curriculum information relates to the current academic year (in most cases).
Course and module offerings and details may be subject to change.

Glossary of Terms

You must earn a defined number of credits (aka ECTS) to complete each year of your course. You do this by taking all of its required modules as well as the correct number of optional modules to obtain that year's total number of credits.
An examinable portion of a subject or course, for which you attend lectures and/or tutorials and carry out assignments. E.g. Algebra and Calculus could be modules within the subject Mathematics. Each module has a unique module code eg. MA140.
Some courses allow you to choose subjects, where related modules are grouped together. Subjects have their own required number of credits, so you must take all that subject's required modules and may also need to obtain the remainder of the subject's total credits by choosing from its available optional modules.
A module you may choose to study.
A module that you must study if you choose this course (or subject).
Required Core Subject
A subject you must study because it's integral to that course.
Most courses have 2 semesters (aka terms) per year, so a three-year course will have six semesters in total. For clarity, this page will refer to the first semester of year 2 as 'Semester 3'.

Year 1 (60 Credits)

Required Core Subject: Data Science (20 Credits):
Required CT1101: Programming I - 5 Credits - Semester 1
Required DSSK1100: Skills for Data Science - 5 Credits - Semester 1
Required CT1102: Programming II - 5 Credits - Semester 2

Optional Subject: Economics (20 Credits):
Required EC1108: Skills for Economics I - 5 Credits - Semester 1
Required EC135: Principles of Microeconomics - 5 Credits - Semester 1
Required ST1112: Statistical Methods - 5 Credits - Semester 2
Required EC136: Principles of Macroeconomics - 5 Credits - Semester 2

Optional Subject: Geography/Tíreolaíocht (20 Credits):
Required TI1100: Geography in Practice - 10 Credits - Semester 1
Required TI150: Principles of Human Geography - 5 Credits - Semester 1
Required TI151: Principles of Physical Geography - 5 Credits - Semester 2

Optional Subject: History (20 Credits):
Required HISK1101: Skills for Historians (1) - 5 Credits - Semester 1
Required HI1103: Europe and Ireland 1789 - 1918 - 5 Credits - Semester 1
Required HISK1102: Skills for Historians (2) - 5 Credits - Semester 2
Required HI1104: Europe: From Medieval to Modern - 5 Credits - Semester 2

Required Core Subject: Maths for Data Science (20 Credits):
Required ST1111: Probability Models - 5 Credits - Semester 1
Required MA185: Analysis and Algebra 1 - 5 Credits - Semester 1
Required MA186: Analysis and Algebra 2 - 5 Credits - Semester 2
Required MA187: Mathematical Skills - 5 Credits - Semester 2

Optional Subject: Philosophy (20 Credits):
Required PI108: Introduction To Practical Ethics - 5 Credits - Semester 1
Required PISK1100: Critical Thinking & Persuasive Writing - 5 Credits - Semester 1
Required PI120: Philosophical Questions & Issues - 5 Credits - Semester 1
Required PI1100: Philosophical Perspectives: A History of Western and Eastern Thought - 5 Credits - Semester 2

Optional Subject: Psychology (20 Credits):
Required PS122: Introductory Psychology 1 - 5 Credits - Semester 1
Required PS1100: Critical and Collaborative Thinking - 5 Credits - Semester 1
Required PS137: Introduction to Research Methods in Psychology - 5 Credits - Semester 2
Required PS124: Introductory Psychology 2 - 5 Credits - Semester 2

Year 2 (60 Credits)

Year 3 (60 Credits)

Year 4 (60 Credits)

Why Choose This Course?

Career Opportunities

Data analytics talent is in very short supply worldwide.  Graduates from this programme will have a highly attractive portfolio of skills, and will be well positioned for a wide range of graduate careers. Those who pursue further study (e.g. NUIGalway’s one-year MSc in Data Science) will be able to apply for data scientist roles. 

Who’s Suited to This Course

Learning Outcomes


Work Placement

The Arts with Data Science degree includes an eight-month off-campus work placement in Year 3. (Should no external placement be available, you will be given a project on campus.)

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

€6,300 p.a. 2019/20

Fees: Tuition

€3,076 p.a. 2019/20

Fees: Student Contribution

€3,000 p.a. 2019/20

Fees: Student levy

€224 p.a. 2019/20

Fees: Non EU

€15,850 p.a. 2019/20
EU Fees 2019/20:
- Tuition: may be paid by the Irish Government on your behalf see - free fee initiative.
- Student Contribution: €3,000 - payable by all students but may by paid by SUSI if you apply and are deemed eligible for a means tested SUSI grant.
- Student Levy:  €224 - payable by all students and is not covered by SUSI.

Find out More

Dr Nick Tosh
t. +353 91 495929
e. nick.tosh@nuigalway.ie


  • Undergraduate Prospectus 2019

    Undergraduate Prospectus 2019 PDF (16MB)

  • Quick Guide 2019

    Quick Guide 2019 PDF (1mb)

  • A Level Guide 2019

    A Level Guide 2019 pdf (1MB)

  • CAO Brochure

    CAO Brochure PDF (1.3 MB)

  • Postgraduate Prospectus 2019

    Postgraduate Prospectus 2019 PDF (12.6 MB)

  • QQI / FETAC Pathways Guide

    QQI / FETAC Pathways Guide PDF (45MB)