Course Overview

This course is a conversion course to enable graduates to take up the increasing opportunities to work as data analysts, who are in demand across multiple sectors, including Financial, Government, Manufacturing, Food, Health and Media.

The course emphasises the development of strong theoretical and applied foundations, and builds on our existing strengths in Data Science and Analytics in the School of Computer Science and the Insight Institute, and our experience in running a successful Masters in Data Analytics.

The programme has a number of core elements:

  • Immersion in fundamental database and software development techniques.
  • A solid foundation in statistical and analysis methods.
  • Expertise in data analysis, visualisation and business intelligence using leading edge tools and programming languages.
  • Capstone project to deepen and demonstrate students’ acquired skills.
  • A significant placement/internship allowing participants to gain relevant experience and also provide Industry Partners with an opportunity to assess potential recruits.

On completion of the programme, graduates will be eligible to take our highly successful MSc in Data Analytics, providing a deeper and more specialised training in advanced Data Science, Machine Learning topics. Transition to this programme is contingent on spaces and achieving a 60% average in the Higher Diploma.

This programme is funded by the Higher Education Authority Human Capital Initiative, Pillar 1*, Graduate Conversion initiative. For applications who are in employment the HEA will fund 90% of the course fee, with the balance to be provided by the application or her/his employer. Recent graduates will also pay 10% of the cost of the course.

*IMPORTANT NOTE: it is envisaged this new HDip course will open to accept applications in May 2020 (check back to this web-site for application-open-date-details), when course funding has been received from the HEA.

Applications and Selections

It is envisaged this new HDip course will open to accept online applications in May 2020 (check back to this web-site for application-open-date-details), when course funding has been received from the HEA.

Who Teaches this Course

Requirements and Assessment

A range of assessment methods are integrated and applied through the programme. These include continuous assessment, projects, reports presentations and case studies.

Key Facts

Entry Requirements

Applicants are normally required to hold a minimum of a Level 8 honours qualification (2.2 or higher) or equivalent in a cognate discipline. Graduates with a Level 7 degree and relevant practical industry experience in the area of computing and information technology will also be considered. Graduates from non-STEM (Science, Technology, Engineering, and Mathematics) disciplines such as languages will be welcomed, but will need to demonstrate an aptitude for logical thinking and problem solving. The application process will include interviews and/or aptitude tests, given that the placement is a key element of the programme.

The programme is in line with the University Policy for Recognition of Prior Learning in that it recognises prior academic qualifications. The aim of this initiative is to provide graduates with the opportunity to acquire qualifications for employment in the data analytics field. RPL applications are also welcome and can be completed by contacting the Programme Director. 

Additional Requirements


1 year, full-time

Next start date

It is envisaged this course will commence in September 2020

A Level Grades ()

Average intake


Closing Date

Please view the review dates website for information.

NFQ level

Mode of study

ECTS weighting




Course code


Course Outline

The programme is delivered over a 12-month period. The first two semesters consist primarily of taught modules, which have a high continuous assessment and practical aspect. The first semester focuses on creating a strong foundation in the Computer Science and Statistical techniques, including: Databases, Internet Programming, Human Computer Interaction, Statistics for Data Science, Programming with Python.

The second semester focuses on deepening skills and applying them to real-life problems. The content includes Applied Data Analytics using the R programming language and packages, further Statistics for Data Science, Data Visualisation techniques and Business Intelligence theory and applications using widely used commercial tools.

A major aspect of the programme is the Industrial Data Analytics Project in which students work on a real-life data analytics and visualisation problem. This work will, where possible, be conducted in conjunction with the work placement company, resulting in the production of the final report and presentation of the project at the end of the work placement. The Work Placement will take place from the end of semester 2 until end August.

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Why Choose This Course?

Career Opportunities

The Higher Diploma in Data Analytics responds to a strong and growing demand for graduates with skills in data analysis across all industry sectors. Every industry has seen a huge growth in the amount of data which they generate and collect, which represents a very valuable resource for companies. Demand for workers with specialist data skills like data scientists and data engineers has increased dramatically over the past five years according to recent surveys. Skills Ireland estimates a demand for Big Data/Analytics roles to the tune of up to 62,000 in Ireland by 2020. Roles that will be suitable for graduates of this programme include: 

  • Data Analysts
  • Data Visualisation Specialists
  • Data Engineers
  • Data Scientists
  • Business Analytics Specialist
  • Business Intelligence Developer

Who’s Suited to This Course

Learning Outcomes


Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

€7,450 p.a. 2020/21

Fees: Tuition

€7,226 p.a. 2020/21

Fees: Student levy

€224 p.a. 2020/21

Fees: Non EU

€20,750 p.a. 2020/21

Find out More

Dr. Owen Molloy
T: +353 91 493 330

School of Computer Science
T: +353 91 493 143 or 493 836


  • Postgraduate Taught Prospectus 2020

    Postgraduate Taught Prospectus 2020 PDF (21 MB)