The course is designed to train healthcare workers without a background in data analytics, statistics, or computer programming. You will learn from domain experts in Clinical Data Analytics from the College of Medicine and Health.

3 modules are completed each semester, each with practical assignments, online learning material, and an end of term in-person exam combined into 1 day at the end of each semester. 

Semester 1:
MD1510 - Fundamentals of Clinical Data Analytics -

Introduction to Health Research, Applied Medical Statistics and Clinical Data Analysis. This module covers topics such as measuring outcomes, formulating a research question and study design, hypothesis test selection and execution, introductory R programming, and the preparation, cleaning and summarisation of health datasets. You will complete a practical assignment, participate in online coding workshops, read several book chapters and research studies, complete lectures and interactive learning content, and a final in-person exam.

Ethical and Regulatory Concepts in Clinical Data Analytics –

MD1511 - Introduction to ethics in clinical research, Good Clinical Practice certification and practice, choosing the appropriate standards to apply in common clinical research studies, writing an ethics application in the Irish context, data standards and practices in the clinical research setting, research integrity training and scenarios, consent requirements and consent declarations. You will complete a practical assignment, read several book chapters, complete lectures and interactive learning content, and a final in-person exam.

MD1512 - Comparisons and Modelling Approaches in Clinical Data Analytics

This module covers topics such as Linking test to data type (excluding time), Linear regression, Logistic regression, Odds ratio, Paired testing (McNemar, paired t-test).

You will use R to create models to describe associations in clinical data. This will include a practical assignment, and more participation in online coding workshops, read several book chapters and research studies, complete lectures and interactive learning content, and a final in-person exam.

Semester 2:

MD1513 - Clinical Data Analytics for Observational and Longitudinal Research Studies

This module covers topics such as the advantages and costs associated with prospective studies, how to examine time related outcomes statistically and how to interpret the results from this. In the R coding class you will be implementing survival analysis, multivariable analysis to account for confounding and you will examine methods to explore non-linear associations. You will complete a practical assignment, participate in online coding workshops, read several book chapters and research studies, complete lectures and interactive learning content, and a final in-person exam.

MD1514 - Applied Clinical Data Analytics Project

You will complete an analysis on clinical data from inception, through statistical analysis plan development, to analysis execution, appraisal, refinement, and reporting. This module is primarily practical, you will have to demonstrate all learning outcomes in this practice.

Projects can be proposed by the applicant, but it is essential that the dataset is sufficient in volume and quality for an ACDA project and that the supervisor has access to the dataset. Projects and datasets can also be supplied by the course team.

AH1500 - Clinical Data Analytics for Healthcare Administrative Datasets & Clinical Audit

This module covers topics including how to characterise data missingness and how to analyse data in the presence of missingness, the biases introduced in routinely collected datasets and how to account for these. Data extraction and cleaning is a core topic as substantial time is lost to this task in analyses of such datasets. This will include a practical assignment, and more participation in online coding workshops, reading several book chapters and research studies, complete lectures and interactive learning content, and a final in-person exam.

Curriculum Information

Curriculum information relates to the current academic year (in most cases).
Course and module offerings and details may be subject to change.

• Course designed specifically for training healthcare professionals in analysis of clinical data.
• This programme is delivered by domain experts in Clinical Data Analytics.
• You will develop profession appropriate, individual, collective and inter-professional data skills.
• The assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.
• You will critique real life case studies and learn by applying statistical tools to work through real data sets.
• You will complete a comprehensive self-directed data analytics project with continuous supervision and feedback.

There are various career paths in healthcare, research, and technology sectors. These roles often require a combination of skills in data analysis, and proficiency in relevant tools and technologies such as statistical software, database management systems, and programming languages like R that is taught on the Applied Clinical Data Analytics Diploma such as clinician scientists in clinical practice engaged in clinical research, designing and executing clinical studies and data analysis.

The Diploma in ACDA aims to enhance the current work of healthcare professionals to become proficient clinical data analyst. Many graduates return to their previous clinical jobs (doctor, nurse, pharmacist) with additional data analytic skills to augment their clinical roles especially with research, audit and quality improvement.

• Prof Martin O'Donnell
• Dr. Sonja Khan
• Dr. Conor Judge
• Dr Alberto Alvarez-Iglesias 
• Professor Andrew Smyth 
• Dr Finn Krewer

The course uses a competency based sequential curriculum for remote learners going from introductory to complicated concepts in clinical data analytics.

There are 3 modules in each of the 2 Semesters, 2 modules per semester are primarily guided while one is self-paced. Each of the 3 modules has practical assignments, and online learning material, videos, and interactive content.

The course is designed to train healthcare workers without a background in data analytics, statistics, or computer programming. You will learn from domain experts in Clinical Data Analytics from the College of Medicine and Health. You will attend an online synchronous coding workshop every 2 weeks for 2 hours.

Each of the 3 modules each semester has an end of term in-person exam, these are combined into 1 day at the end of each semester.

Some of the in-person exams will be written and some are oral such as presentation or interactive oral assessment.

For general queries, please contact:

E: clinicaldataanalytics@universityofgalway.ie

Programme directors
Dr Conor Judge,
School of Medicine
E: conor.judge@universityofgalway.ie

Dr Sonja Khan,
School of Medicine
E: sonja.khan@universityofgalway.ie

Q. How often will I need to attend classes in Galway?
A. In Semester 1, you’ll take three core modules:
Fully Online.  There is an in-person exam 1 day at the end of each semester.

Q. Is there any financial assistance available for this programme?
A. The programme itself doesn’t offer direct financial aid. However, funding opportunities are available through the University of Galway. Please visit:
  University of Galway Financial Aid

Q. Do I meet the entry requirements?
A. Students must have completed one of the following:

1. An undergraduate degree in Nursing, Pharmacy, Physiotherapy, Medicine.
2. Another healthcare-related undergraduate degree with a minimum of 2nd Class Honours.
3. A biomedical related undergraduate degree with a minimum of 2nd Class Honours.

Applicants from non-healthcare related degrees will be considered on a case-by-case basis at the discretion of the coordinators (minimum requirement of 2nd Class Honours). Applicants with significant relevant experience will also be considered.

Q. When is the application deadline?
A. The deadline is August 2026 .
We recommend applying early, as places may fill before the official deadline.
Apply here: Application Portal

Q. When does the course start?
A. The Diploma in Applied Clinical Data Analytics starts in early September.
Check the academic calendar for specific dates: Academic Calendar

Q. Are there multiple admission intakes per year?
A. No, admissions occur once a year.

Q. Do I need to take IELTS if I did my MBBS in English?
A. If your MBBS degree was taught in English, IELTS is not required. 

Q. Which transcripts should I submit with my application?
A. Submit transcripts from your most recent degree.

Q. How competitive is this programme?
A. We accept: 10 full-time students

Applicants are assessed based on academic record and personal statement.

Q. What are the career prospects?
A. There are various career paths in healthcare, research, and technology sectors. These roles often require a combination of skills in data analysis, and proficiency in relevant tools and technologies such as statistical software, database management systems, and programming languages like R that is taught on the Applied Clinical Data Analytics Masters.

Additionally, staying updated with advancements in healthcare regulations and technologies is crucial for success in these careers. 

Q. Where can I find fee details?
A. Visit the University’s Fees Office:
 Postgraduate Fees Info

 

Students must have completed one of the following:

1. An undergraduate degree in Nursing, Pharmacy, Physiotherapy, Medicine.
2. Another healthcare-related or health and social care professional undergraduate degree with a minimum of 2nd Class Honours.
3. A biomedical related undergraduate degree with a minimum of 2nd Class Honours.

Applicants from non-healthcare related degrees will be considered on a case-by-case basis at the discretion of the coordinators (minimum requirement of 2nd Class Honours). Applicants with significant relevant experience will also be considered.

For PG Diploma Applied Clinical Data Analytics Online at the University of Galway, applicants must meet one of the following English language requirements: Academic IELTS (including IELTS Online) with an overall score of 6.5 and no less than 6.5 in any component; Cambridge C1 Advanced (CAE) with an overall score of 176; Cambridge C2 Advanced (CPE) with an overall score of 180; TOEFL iBT or TOEFL iBT Home Edition with an overall score of 88, including Listening 20, Speaking 20, Writing 24, and Reading 19; or Pearson PTE Academic with an overall score of 61 and no less than 61 in any component.

Applicants who do not meet the primary entry criteria as described above will be declined entry into the program. The remaining applicants will be reviewed in closer detail, with significant weight placed on: A) The applicant’s essay describing their motivation for applying to this course and their career aspirations following the successful completion of the MSc. B) The applicant’s previous academic performance. C) The applicant’s referee’s comments.

This programme is NOT eligible under the Interim List of Eligible Programmes (ILEP).

*Or equivalent international qualification

Applications will open in early 2026, please express your interest on this form below: OFFICE form link and we will contact you when applications formally open.

Fees for Academic Year 2027/28

Course Type	Year	EU Tuition	Student Contribution	Non-EU Tuition	Levy	Total Fee	Total EU Fee	Total Non-EU Fee
PG Diploma FT	1	€6300	€0	€16450		€0	€6300	€16450
PG Diploma FT	1	€6100		€16000			€6100	€16000
PG Diploma FT	1	€6,100		€16,000			€6,100	€16,000

Application Process

Students applying for full time postgraduate programmes from outside of the European Union (EU), You can apply online to the University of Galway application portal here. 

Our application portal opens on the 1^st October each year for each the following September.  

Further Information

Please visit the postgraduate admissions webpage for further information on closing dates, documentation requirements, application fees and the application process.

For general queries, please contact:

E: clinicaldataanalytics@universityofgalway.ie