Courses in


Higher Diploma in Science in Computing (Data Analytics) - ICT SKILLS/SPRINGBOARD+

Discipline: Science

Programme Code: 


Location: Online

NFQ Level: 8

Mode of Study: Online delivery

Entry Requirements: Level 8 Honours Degree (or equivalent if earned outside the EU - see

Credits: 75

Places: 50

CAO Round 1 Points: Not applicable

Why Study?

  • You are a Level 8 Graduate from a non-computing background who wishes to enter into a career in computing.
  • The aim of the course is to provide you with a broad knowledge of computing, with a specialisation in data analytics.
  • This will enable you to apply data analysis techniques to the topics in your original degree.
  • It will also provide you with a foundation on which you can develop your skills in the more traditional areas of computing.
  • This course is fully online.

The course covers such skills as automating manual spreadsheet-oriented data analysis processes, converting large data sets into actionable information, and creating web-based dashboards for visualising data.


NOTE: This course is now closed for applications.

If approved under Springboard+, it will open for applications on in May/ June 2021.

The start date if approved would be January 2022.

Please monitor the and website for updates.

Programme Modules

The subjects undertaken are as follows:

  • Data Representation and Querying (5 credits at Level 8)
    In this module students will investigate and operate the protocols, standards and architectures used in representing and querying the data that exists across the internet.
  • Programming and Scripting (10 credits at Level 8)
    An in-depth introduction to computer programming and scripting.
  • Fundamentals of Data Analysis (5 credits at Level 8)
    In this module, students learn about the basics of data analysis and its underlying mathematical concepts.
  • Computer Architecture and Technology Convergence (5 credits at Level 8)
    This module covers the basic principle of traditional computer design and highlights current trends in mobile and pervasive computing architectures.
  • Computational Thinking with Algorithms (5 credits at Level 8)
    This module provides detail of algorithm design and the computational problem solving process using programming libraries and application programming interfaces (APIs).
  • Programming for Data Analysis (10 credits at Level 8)
    In this module, students develop their programming skills towards the effective use of data analysis libraries and software.
  • Object Oriented Software Development (5 credits at Level 8)
    This module provides an introduction to programming (using an Object-Oriented approach) and assumes little or no previous experience in programming.
  • Machine Learning and Statistics (5 credits at Level 8)
    A practical look at the most popular algorithms used in machine learning and the analysis of stochastic processes.
  • Web Applications Development (5 credits at Level 8)
    This module is focused on the development of practical skills in the area of web applications.          
  • Advanced Databases (5 credits at Level 8)
    This module presents the theory and practice relating to advanced database applications in areas such as Enterprise Data Management, and in the management and storage of non-relational data.
  • Work Placement/ Project (15 credits at Level 8)
    Work placement is undertaken only by Unemployed applicants, otherwise a Project is undertaken. Such candidates will be assigned a dedicated academic supervisor for the duration of the project.


Career Opportunities

Data Analytics/Data Science is a growing area of employment, with significant future growth also anticipated.

This is well established in various national skills bulletins (e.g. Expert Group on Future Skills Needs).

Follow-on Studies: 

A sufficient result on this course would qualify students to undertake Level 9 (Master) programmes.

Essential Information: 


To apply, go to

Choose either the part-time course (18-24 months) or the full-time course (12 months). Unemployed applicants must choose the full-time course (12 months) to qualify for the Back To Education Allowance.

You cannot apply via


To complete your application process, you must upload the following:

  • A scanned copy of your EU Passport, or a scanned copy of your non-EU Passport with a copy of your Stamp 4 visas since January 2017.
  • A copy of your Curriculum Vitae.
  • A copy of your Level 7 Degree/Major Award or highest other qualification. Translated if not in English.

You must also upload ONE of the following:

  • A scanned copy of a recent payslip if employed showing your PPSN, OR
  • A scanned copy of a recent payment slip if in receipt of jobseekers allowance/benefit, OR
  • A copy of a recent bank statement showing receipt of a different, eligible, Department of Employment Affairs & Social Protection payment, OR
  • A letter from your accountant confirming that you are self-employed, OR
  • An affidavit signed by you and the appropriate third-party confirming that you are a homemaker.



Fully online, your attendance at GMIT is not required.



A 10% contribution (appro €675) is required from employed applicants. This course is free to unemployed applicants.


Part-time Mode: January 2021 – May 2022 (18 months - can be extended to 24 months)

  • Semester 1: Jan 2021 - May 2022 (20 credits)
  • Semester 2: Sep 2021 - Dec 2021 (20 credits)
  • Semester 3: Jan 2021 - May 2022 (20 credits)


Full-time Mode: January 2020 – May 2021 (12 months - for unemloyed applicants who need to complete it in 12 months to qualify for the BTEA)

  • Semester 1: Jan 2021 - May 2021 (30 credits)
  • Semester 2: Sep 2021 - Dec 2021 (30 credits)

Eligibility criteria:

See eligibility section of


Recognised Prior Learning

Recognised Prior Learning applications will be considered from those holding a Level 7 degree (60 credits at Level 7) plus a minimum of 3 years working experience.


The Springboard+ Programme is operated by the Higher Education Authority on behalf of the Department of Education and Skills and is co-funded by the Irish Government and the European Union under the Euroepan Structural and Investment Funds Programme 2014-2020.

Contact Us

Peer Butler
Graduate Studies and Professional Development
Galway Mayo Institute of Technology
Dublin Road

Tel: +353 (0)85 805 3691 (Mon-Fri, 9-5)

Springboard+ is co-funded by the Government of Ireland and the European Social Fund as part of the ESF programme for employability, inclusion and learning 2014-2020