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Accessibility & LanguageMSc (Applied Clinical Data Analytics)
College of Medicine, Nursing, & Health Sciences, Medicine
Course Code: ACA1; ACA2
Course Overview
The taught postgraduate course in Applied Clinical Data Analytics employs a unique and innovative spiral curriculum, designed specifically for training healthcare professionals in analysis of healthcare data. Domain experts in Clinical Data Analytics from the College of Medicine, Nursing and Health Sciences will deliver the program. Assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.
- The course is designed to train healthcare workers without a background in data analytics, statistics, or computer programming, to analyse and interpret healthcare data.
- Applies research and data analytics knowledge to clinical and health data to effectively answer research questions.
- We will teach students to understand and learn how to apply traditional statistical techniques and machine learning by completing weekly assignments and an end of year thesis.
- Students will learn data import, cleaning, exploration and analysis using the R programming language and R packages for data analysis, machine learning and source control using GitHub.
- We will teach research methodology and appropriate statistical analysis using R for randomised controlled trials, systematic reviews, case control studies and prospective cohort studies.
The Applied Clinical Data Analytics Masters was a 2024 finalist in the Irish Healthcare Centre Awards in Education, Learning & Development. This recognition is a testament to the hard work, dedication, and innovative spirit of every member of our team. Being named a finalist reaffirms our commitment to excellence in training healthcare professionals in the analysis of healthcare data.
Pictured Left to Right: Honor Griffin, Dr. Alberto Alverez-Iglesias, Dr. Conor Judge, Dr. Sonja Khan, Dr. Finn Krewer.
Applications and Selections
Who Teaches this Course
Requirements and Assessment
Figure 2—Term Overview for MSc Applied Clinical Data Analytics (part-time)
Newsletter
What Experts Say
Prof Pavel Roshanov | External Examiner, MSc Applied Clinical Data Analytics.
Health and healthcare data are ever more plentiful, statistical software is free, and access to theoretical knowledge is available to everyone on the web, but the opportunity for apprenticeship with experts who combine clinical domain knowledge with statistics and research methodology is deeply valuable and hard to find. The new MSc in Applied Clinical Data Analytics combines traditional research methodology training with clinical data analytics through the R statistical programming language. It is taught directly by clinical researchers with backgrounds in epidemiology and data analytics who teach statistics and analytics in the research context where they will be used. This is a fantastic programme.in Connect with Prof Pavel
What Our Students Say
Aoife Boyle | Applied Clinical Data Analytics Student
Embarking on the Masters course in Applied Clinical Data Analytics has significantly enhanced my understanding of health research and critical analysis. The course has equipped me with the ability to scrutinise complex health data with precision and insight. My theoretical knowledge is now solidly underpinned by practical analytic skills, acquired through hands-on database analytics. I am excited to harness both facets of my skillset to advance my career as a clinical pharmacist in promoting evidence- based medicine in critical care and increase my involvement in the analytics of electronic datasets.
Dr. David Agular | Applied Clinical Data Analytics Student
During the MSc programme in Applied Clinical Data Analytics, I have come to understand the relationship between data analysis and various facets of research. From designing and implementing research methodologies to ensure data integrity and quality, to selecting and reporting analysis methods, this programme has equipped me with the necessary tools to produce reliable and comprehensible research outcomes. The practical approach of this programme, combined with the support and mentorship from faculty members, allowed me to cultivate a deeper proficiency in the different domains of data analysis, motivating me to pursue my academic and professional aspirations.
Dr. Reginald Cadlecott | Anaesthetist and Intensivist Registrar
Studying the MSc in Applied Clinical Data Analytics at Galway University has been a game-changer for me. As a Clinical Tutor in Anaesthetics, I use the skills I gained from the course every day—whether it’s in research, mentoring, or working on projects like the ESICM Datathon. The programme gave me the confidence and tools to dive into clinical data, make sense of complex datasets, and apply analytics in a way that improves research and patient care. The blend of practical applications with a strong theoretical foundation meant that I wasn’t just learning concepts—I was developing real-world skills that I could immediately use. I now have a structured way to analyse clinical data, which has allowed me to contribute more effectively to research and even develop new publications using digital resources and advanced analytical techniques. Balancing clinical work with academic study is never easy, but the course was designed in a way that made it manageable—even enjoyable. The lecturers were incredibly supportive, and learning alongside other healthcare professionals meant that discussions were always relevant to real-world challenges.in Connect with Dr. Reginald
Dr. Clodagh McDermott | Applied Clinical Data Analytics Student
The Master's in Applied Clinical Data Analytics provided me with a solid base to undertake my PhD in stroke medicine and machine learning. The masters offered me a solid foundation in clinical research through a focused and practical approach to applying data analytics and machine learning methodologies to real-world research questions. The blended approach to teaching research methodologies, statistics, and R programming significantly enhanced my learning experience. I not only gained competency in the R programming language, but I also developed a deeper understanding of its applications in data analysis, data visualisation, and machine learning; all skill-sets crucial for the modern medical researcher. The course content was thoughtfully developed, striking a balance between challenging and engaging content. My learning was supported by experienced, dedicated, and approachable lecturers who fostered a friendly learning environment. The Master's in Applied Clinical Data Analytics surpassed my expectations and has equipped me with invaluable skills and knowledge. For those aspiring to excel in healthcare research, this programme is an excellent choice.
