Our Research Group

The TU Dublin – Blanchardstown campus Data Science Research Group is a vibrant community of experienced researchers that span a range of data science domains. Particular interests include:

  • Educational and psychometric data analytics, including accessible learning analytics for higher education and analysis of organisational silence
  • Unstructured web content & social media content
  • Data science in transportation
  • Text analytics in healthcare
  • Image and video analysis, including sign language analytics
  • Geospatial data analysis
More information on our Research Group
View Our List of Publications

Our taught masters programme

Our Master of Science in Computing in Applied Data Science & Analytics is a part-time programme that runs fully online,  designed in collaboration with industry partners. It has gained a significant reputation for high quality content that combines a practical focus with technical depth and rigour. There is a strong demand for our graduates in sectors where data science and big data analytics is a critical component, such as the insurance, retail, pharmaceutical, biotechnology, business, travel, telecommunication, government, and intelligence sectors.

Lectures are delivered live, two evenings a week (Dublin time), using an online classroom environment. This, coupled with lecture recordings and other learning resources accessible via our Virtual Learning Environment, provides a truly flexible learning environment for all participants. Course modules are assessed through continuous assessment only, allowing students not resident in Ireland to complete the course.

More information on our Masters programme

Data Science and Analytics is one of the fastest growing areas of IT, across a variety of organisations and industries, and remains mission critical for businesses as it turns information into an asset for deriving insights and making decisions. The high demand for graduates from this our MSc reflects the need for companies to do business more smartly, enabled by data science.

“To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science.”



Here is what our students said about our MSc programme:

Thank you for all your work co-ordinating the MSc programme, your taught modules and being my supervisor for the 1st year project! It has been a wonderful experience which I’m very grateful for and has been extremely valuable for my professional career also.


Many thanks for your input into the project and teaching over the past two years; very happy with what I learned from all the modules and the final results.


The number of technical universities that offer part-time master’s degrees in Data Science is rather low. This number becomes even smaller if we disregard all part-time master’s degrees that require (partial) on-site attendance to complete the course. Therefore, I have to express my deepest gratitude to Dr. Geraldine Gray and Dr. Markus Hofmann for developing a full online master’s course in Applied Data Science and Analytics of such a high quality standard. The Master of Science in Applied Data Science and Analytics at TU Dublin Computer Science is characterized by its focus on deep understanding and practical problem solving. Without this wonderful program I may never have completed my master’s that I originally started at the University of Bielefeld before transitioning to Technological University Dublin.

I wanted to thank you three for all the effort you put in. It’s tough running college classes when you can’t even have spoken interaction but you did a great job on structure, materials and delivery. From the people here at work who have done similar courses, the consensus was that a lot of the other data analytics masters have a lot more “fluff or filler” in them whereas the TU Dublin one is more practical.
Finally, I just wanted to say thanks for all your support. Of all the college courses I have done, I enjoyed this one the most and would highly recommend it but that is mainly down to you three. Thanks again.

My company has been doing some analysis on the monetary value of my Thesis work to the company. As I say, it’s conservative – the real extra savings number is probably worth north of $20 million.


I had noticed that tools in Data Mining could be used to learn clusters and hence to automate my work tasks. I decided to take the course and to go a little deeper . Since I took the course, I have been able to exploit many algorithms to learn patterns and hence assign labels/categories to things in a highly automated way. In addition to the new skills learned I managed to re-kindle skills in Analytics, Software Engineering, Big data and visualisations that I had worked on before, but the course also helped me to hone these skills.
The lectures were delivered online so there was no need to attend in person, but there was always the option to arrange a meeting with a tutor or project supervisor if you so wished or needed that extra support. Each evening is recorded and available on Moodle and hence you never really lose out if you have a conflict. You can listen to the lecture when it suits you. Although, if you wish to ask a question it is best to try to attend on the event.
When combining a day job with a course, it is essential to have a clear line of sight of activities due at the start of each module. The roadmap is very clearly set-out at the beginning of a module and there was a definite plan for the activities. The course is exciting. If your work life involves Spreadsheets, SQL statements, VLOOKUP, PowerPoint charts, then this course is for you. The course allows you to update your skills and knowledge in a field that is currently very popular. Deep Learning, Advanced Analytics, Predictions, Scoring, ETL (extract transform load) and visualisations will be demonstrated to you naturally and understandably. You will gain practical experience, do projects and importantly be able to use these techniques in your day job. The highlight for me was doing the Research Project and taking final delivery of my Thesis.
I enjoyed the course and gained a tremendous benefit from doing it. I feel so much more confident now tackling big data jobs, drawing charts, or using Predictive Analytics.


It was one of my best decisions to embark on an MSc. It is undeniably a lot of work so it is important to be interested in the subject but even I was surprised how I took to it and how much work I put into it without realising. It has already opened some new possibilities and it will lead on to interesting career opportunities.


Thank you and Markus also for all your help and advice over the past two challenging but very rewarding years.