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Higher Diploma in Data Analytics

QQI Level 8
  • Awarded by QQI (Quality & Qualifications Ireland)
  • Full-time/On Campus
  • Duration 12 months (1 Academic Year)
  • Starting 23rd September

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The Higher Diploma in Data Analytics is a one-year (60 credit) Higher Diploma programme that is awarded at Level 8 on the National Framework of Qualifications

This Higher Diploma delivers essential knowledge and skills in modules related to Data Analysis for learners who wish to become experts in this high-demand, fast moving technology area. The programme aims to develop learners’ knowledge of both the theory and practice of Data Analytics necessary for them to gain professional employment and succeed as graduate-level practitioners in a broad range of environments. Learners will build upon fundamental theoretical knowledge, so that they can apply advanced analytics skills to modelling, statistics, programming, machine learning, and advanced visualisation of data sets through the use of a variety of tools and techniques, in order to generate actionable insights for stakeholders and support strategic decision making.

The objectives of the programme are to:

  1. Support learners to develop the Data Analysis skills necessary to develop a career in this area;
  2. Develop the learner’s ability to investigate, critique, evaluate and analyse theories, concepts, techniques and models to identify and implement solutions to data related problems;
  3. Enhance the learner’s knowledge of the interrelationships and inter dependences of the various data functions;
  4. Provide a learning environment that encourages and supports education at a Higher Diploma in Science level;
  5. Provide learners with the opportunity to progress to further education at Level 9 or seek exemptions from one of the professional bodies (e.g the analytics institute of Ireland);
  6. Broaden the learner’s knowledge of Data Analytics so that they may be in a position to generate new knowledge and methodologies with their advanced skillset;
  7. Provide learners with an environment that develops and supports time management, advanced reflection, data management skills that are necessary in the workplace.
  • 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

This programme will be offered full-time, delivered from our main campus building on South Great George’s Street, Dublin 2. Lectures will be delivered, typically, over three full days between 9am and 5pm, a provisional timetable will be available in the coming weeks. The programme takes one academic year to complete.

To be considered for admission to this programme, applicants must hold a Primary Honours Degree (level 8) in a non cognate discipline from a recognised third level institution or equivalent qualification.

Candidates will ideally be able to demonstrate technical or mathematical problem solving skills as part of previous programme learning. Typically holders of more technical, numerate degrees are likely to gain a higher ranking in any order of merit in selection for the programme.

Recognition of Prior Learning (RPL)
Learners may also access this course on the basis of recognition of prior learning or by assessment of prior experiential learning/informal learning. The process is implemented within the relevant school, by the relevant Head of School/Department or nominee and is overseen by the Registrar. For this particular programme applicants will be considered on a case-by-case basis based on their educational record, work experience, their ability to demonstrate technical or mathematical problem solving skills and a capacity to successfully participate in the programme.

For applicants whose first language is not English, a B2+ in CEFRL (IELTS Academic score of 6.0, or equivalent), is needed.

Location: On Campus, Dublin 2

Timetable: Typically, 3 full days per week, lectures scheduled between 9am and 5pm, delivered over 2 semesters or 1 academic year

Suitable for:

  • Holders of hold a Primary Honours Degree (level 8) in a non cognate discipline from a recognised third level institution or equivalent qualification


  • €5,800 – Irish/European Nationals
  • €5,800 – Non-EU nationals residing in Ireland (stamp 2)
  • €8,200 – Non-EU applicants applying from outside of Ireland

All fees are payable per academic year of study.

Candidates wishing to apply should complete the following online application form.

Once the application is submitted a member of the Admissions team will be in contact with you within 1-3 working days to advise you on the next steps to enrolment.

Alexander Mutiso

Alexander Mutiso Mutua is a PhD researcher at Technological University Dublin. He holds a Bachelor’s degree in Computer Science from Kisii University in Kenya and a Master’s degree in Advanced Computer Science from Swansea University in the United Kingdom. He has a strong background in computer science and has worked in the telecommunications industry where he has gained experience in various fields, such as big data analytics, machine learning and computer vision. Alexander is passionate about teaching and sharing his knowledge with others
His motivation is to bridge the gap between theoretical insights and real-world applications to students, by leveraging his extensive industry and academic experience.
Alexander’s research interests include machine learning and artificial intelligence, big data, data mining and computer vision 

Neeraj Jha

An Analytically driven Strategic Management professional with over 14 years of experience in solving business problems through data driven insights in Strategic Management areas within Aviation, Travel Technology & Industrial Manufacturing industries in the geographies of Asia, Europe and Middle East regions. Successfully led large scale Analytics and Data Management functions with companies like Honeywell, TUI Group, Smartbox Group & Go Airlines within Ireland, UAE, Spain, Singapore & India.

Neeraj is currently undergoing an M.Phil research in the field of Business Resilience, his prior educational background includes a Post Graduate Diploma in Business Resilience from Dublin Ireland, complemented by an MBA and BS (Computer Science & IT) Degrees from India.

James Lunt

James is a Masters graduate in Computer Science from Trinity College Dublin. His research consists of distributed AI techniques in medical image-classification, specifically for the diagnosis of Cardiovascular Disease. He has also worked as a Software Developer for top tech companies such as Guidewire Software & Microsoft

Aidan Pender

Aidan holds an MBA and boasts diverse qualifications spanning Business Management to Data Analytics.
He successfully completed his own Higher Diploma in Data Analytics with DBS.

Over the past decade, his focus has been primarily on Finance in the Tech industry, working for renowned companies such as Facebook and DocuSign.
For the last 2 years, he has been a part of Twilio’s Finance department.

Sabarish Nair

Why Study This Programme?

Data is the lifeblood of many industries and understanding how to process, analyse and visualise that data is a skill much sought after by employers. The Diploma in Data Analytics is aimed at people who want to learn these skills and advance their career prospects. It’s also great if you work with data and want to boost your knowledge of analytics tools and processes to improve your overall productivity.

Who Is This Programme For?

The Diploma in Data Analytics is a one-year (60 credit) Special Purpose Award (SPA) programme that is awarded at Level 8 on the National Framework of Qualifications.

This diploma provides comprehensive coverage of the key aspects of the Data Analytics industry. It aims to deliver an in-depth analysis of the core issues that parties typically encounter in Data Analytics.

This course is intended for anyone who wants to take the data analysis technologies in Excel and similar Analysis Tools beyond formulas and add more advanced capabilities such as dashboards, hierarchies, and relationships.

Further Information

Please call the College on +353 1 416 0034 or email

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