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
Course applications are then made online via the University of Galway Postgraduate Applications System.
Who Teaches this Course
1. Spotlight on Staff
Introducing some of the teaching staff of the Applied Clinical Data Analytics Masters programme: https://stories.universityofgalway.ie/introducing-our-teaching-team-acda/index.html
The Future of AI in Medicine
AI has massive potential to revolutionise and better medical care. However, it is not without its risks. In this TEDx Talk Dr Conor Judge,Co-Director & Senior Lecturer, Applied Clinical Data Analytics, and Consultant Nephrologist at Saolta University Health Care Group highlights what is needed in order to implement multimodal AI safely into the healthcare system.
View the Ted Talk here
2. A message from Co-Directors
Dr Conor Judge and Dr Sonja Khan and Team
The role of clinical health data has become increasingly more important, offering insight into patient care, operational efficiency, and clinical research. Through this postgraduate taught Master’s programme we will equip healthcare professionals with health data analytics and research methodology skills to navigate this evolving landscape with confidence and knowledge. Students will learn how to ask and answer a research question using health data, code using the R programming language, the fundamentals of research methodology, an applied understanding of medical statistics, and how to create publication ready tables and figures. We are looking forward to welcoming our second student cohort in September 2024, the team are committed to fostering an inclusive and supportive learning environment.
3. Healthcare Centre Awards Finalist 2024
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
Requirements and Assessment
Assessment is via a combination of continuous assignments (70% and written exams (30%, that will be 100% computer-based assessment.
