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Accessibility & LanguageApplied Clinical Data Analytics (MSc)
MSc (Applied Clinical Data Analytics)
College of Medicine, Nursing & Health Sciences, School of Medicine- Title of Award
- Master of Science
- Average Intake
- 15
- Delivery
- On Campus
- NFQ
- Level 9
- Award Type
- Major
- Next Intake
- September 2025
- Duration
- 1 year, full-time, 2 years, part-time
- ECTS Weighting
- 90
Why Choose This Course?
Course Information
Who is this course for?
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.
The course is designed to teach students without a background in data analytics, statistics, or computer programming, to analyse and interpret healthcare data.
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.
What will I study?
The course is designed to train healthcare workers without a background in data analytics, statistics, or computer programming, to analyse and interpret healthcare data.
- You will learn from domain experts in Clinical Data Analytics from the College of Medicine, Nursing and Health Sciences.
- You will learn to apply research and data analytics knowledge to clinical and health data in order to effectively answer research questions.
- You will learn how to apply traditional statistical techniques and machine learning methods by completing weekly assignments and an end of year thesis. Assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.
- You will learn how to import data, conduct data cleaning, exploratory data analysis and how to develop and execute statistical analysis plans using the R programming language and R packages for data analysis, machine learning and how to use source control using GitHub.
- You will learn health research methodologies and appropriate statistical analysis using R for randomised controlled trials, systematic reviews, case control studies, and prospective cohort studies.
Curriculum Information
Curriculum information relates to the current academic year (in most cases).Course and module offerings and details may be subject to change.
Glossary of Terms
- Credits
- You must earn a defined number of credits (aka ECTS) to complete each year of your course. You do this by taking all of its required modules as well as the correct number of optional modules to obtain that year's total number of credits.
- Module
- An examinable portion of a subject or course, for which you attend lectures and/or tutorials and carry out assignments. E.g. Algebra and Calculus could be modules within the subject Mathematics. Each module has a unique module code eg. MA140.
- Subject
- Some courses allow you to choose subjects, where related modules are grouped together. Subjects have their own required number of credits, so you must take all that subject's required modules and may also need to obtain the remainder of the subject's total credits by choosing from its available optional modules.
- Optional
- A module you may choose to study.
- Required
- A module that you must study if you choose this course (or subject).
- Required Core Subject
- A subject you must study because it's integral to that course.
- Semester
- Most courses have 2 semesters (aka terms) per year, so a three-year course will have six semesters in total. For clarity, this page will refer to the first semester of year 2 as 'Semester 3'.
Year 1 (90 Credits)
RequiredMD1592: Clinical Data Analytics I - 10 Credits - Semester 1RequiredMD1596: Clinical Data Analysis Thesis Part I - 10 Credits - Semester 2
RequiredMD1590: Health Research Methodology I - 10 Credits - Semester 1
RequiredMD1591: Applied Medical Statistics I - 10 Credits - Semester 1
RequiredMD1597: Clinical Data Analysis Thesis Part II - 20 Credits - Semester 2
RequiredMD1595: Clinical Data Analytics II - 10 Credits - Semester 2
RequiredMD1594: Applied Medical Statistics II - 10 Credits - Semester 2
RequiredMD1593: Health Research Methodology II - 10 Credits - Semester 2
- Unique and innovative spiral curriculum, 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 Masters.
Here are some roles aligned to the Masters:
- Clinical Data Analyst: They analyse healthcare data to improve patient care, streamline operations, and support decision-making processes within clinical settings.
- Healthcare Data Scientist: Leveraging advanced statistical and computational techniques, they analyse complex healthcare data to derive insights, predict trends, and develop data- driven solutions for healthcare challenges.
- Clinical Informatics Specialist: They focus on integrating healthcare data with information technology systems to improve the efficiency and quality of healthcare delivery.
- Clinical Research Coordinator: Responsible for managing and analysing data collected during clinical trials, ensuring compliance with regulatory requirements and ethical standards.
The MSc in ACDA also 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.
How will I learn?
Full-time students must complete six core modules (Figure 1) across semester 1 and 2 worth 60 ECTS. Students are also required to complete a Thesis project (30 ECTS) split into two parts. Part-time students complete this program over 2 years, completing 40 ECTS in year 1 and 50 ECTS in year 2 (Figure 2).
Range of Teaching/Formal Learning:
Tutorial-based teaching, flipped classroom, problem-based learning, real life case studies will be examined and critiqued, and students will learn by applying statistical tools to work through data sets.
Research project:
Self-directed research project with continuous supervision and feedback. Deadline for write up is at the end of July.
Figure 1- Term Overview for MSc Applied Clinical Data Analytics (full-time)
Figure 2- Term Overview for MSc Applied Clinical Data Analytics (part-time)
Applied Clinical Data Analytics Summer School 2025
We're absolutely delighted to conclude another outstanding year for our Applied Clinical Data Analytics Summer School at the University of Galway. Our annual summer school is as an excellent introduction to the field of Clinical Data Analytics and gives a small taster of the kind of analyses and study designs that students will learn about in the MSc in Applied Clinical Data Analytics.
This year from June 11th-13th, we brought together 50 Clinicians, Health and Social Care Professionals, and University of Galway Researchers for three intensive days of lectures and hands-on R workshops.
A heartfelt thank you to all participants, faculty, and supporters who made this year's programme such an extraordinary success!
The Education Awards 2025
The Programme was a Finalist for the Best Masters Programme at the 2025 Education Awards. This distinction underscores the programme's exceptional quality and innovative approach to healthcare education. The Education Awards recognition serves as a testament to the hard work, dedication, and innovative spirit of every member of the team and reaffirms the programme's commitment to excellence in training healthcare professionals in the analysis of healthcare data, positioning graduates for diverse career opportunities in clinical data analysis, healthcare data science, and related fields.
The Irish Healthcare Centre Awards 2024
The Team attended the 2024 Irish Healthcare Centre Awards as finalists.
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.
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 over 12 weeks:
- On Campus, Tuesdays (9am to 11am), Thursdays (4pm to 6pm), Fridays (9am to 11am).
- All modules require in-person attendance.
- Attendance in second semester is identical.
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 with a 2.1 Honours?
A: Students must have completed one of the following:
- An undergraduate degree in Nursing, Pharmacy, Physiotherapy, Medicine.
- Another healthcare-related undergraduate degree with a minimum of 2nd Class Honours.
- 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 July 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 MSc 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: Are scholarships available?
A: Yes. Some options include:
- International Scholarships
- Government of Ireland International Education Scholarships
- International Office: International Students
Q: What is the ACDA Fellowship?
A: Subject to funding and resources, fellowship opportunities are available. These fellowships aim to provide students with a unique opportunity to gain hands-on experience in Applied Clinical Data Analysis at the Clinical Research Facility, Galway.
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: Can I work part-time while studying?
A: We advise against full-time employment while pursuing the MSc full-time.
Q: Is student accommodation available?
A: Yes. Options include:
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:
- 20-25 full-time students
- Applicants are assessed based on academic record and personal statement.
Q: Are there opportunities to network with professionals?
A: Yes, we regularly host guest lectures and seminars by professionals in clinical research and data analytics.
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: Does the University help with job placement?
A: The Career Development Centre offers workshops and job alerts. Career Services.
Q: What is the typical career path for graduates?
A: Here are some roles aligned to the Masters:
- Clinical Data Analyst: They analyse healthcare data to improve patient care, streamline operations, and support decision-making processes within clinical settings.
- Healthcare Data Scientist: Leveraging advanced statistical and computational techniques, they analyse complex healthcare data to derive insights, predict trends, and develop data-driven solutions for healthcare challenges.
- Clinical Informatics Specialist: They focus on integrating healthcare data with information technology systems to improve the efficiency and quality of healthcare delivery.
- Clinical Research Coordinator: Responsible for managing and analysing data collected during clinical trials, ensuring compliance with regulatory requirements and ethical standards.
Q: How can I make the most of the course?
A:
- Engage with peers and lecturers
- Attend seminars and tutorials
- Choose your thesis topic early and align with a supervisor’s area of expertise
Q: Should I apply for the course or scholarship first?
A: Apply for the course first.
Once accepted, you can apply for available scholarships. More info: Postgraduate Scholarships How to Apply
Q: Where can I find fee details?
A: Visit the University’s Fees Office: Postgraduate Fees Info
Accreditations & Awards
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Embarking on the Masters 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.
Aoife Boyle
Student
During this masters, 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, 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 aspirations.
Dr. David Agular
Student
Studying the MSc in Applied Clinical Data Analytics at has been a game changer. As a Clinical Tutor in Anaesthetics, I apply the skills daily in research, mentoring, and projects like the ESICM Datathon. The course gave me the confidence to explore complex datasets and use analytics to improve both research and patient care. Its blend of practical applications and theoretical foundations helped me develop real-world skills. Balancing clinical work with study was manageable, thanks to the supportive lecturers. I feel better equipped to lead and contribute to data-driven healthcare initiatives.
Dr. Reginald Cadlecott
Anaesthetist and Intensive Specialist Registrar
The MSc in Applied Clinical Data Analytics gave me a strong foundation for my PhD in stroke medicine and machine learning. Its focused, practical approach helped me apply analytics and machine learning to real research problems. The blend of research methods, statistics, and R programming deepened my skills in data analysis, visualisation, and machine learning. The content was well-designed and supported by approachable lecturers. This programme exceeded my expectations and is ideal for anyone pursuing healthcare research.
Dr. Clodagh McDermott
Student
Meet our Employers
Entry Requirements and Fees
Students must have completed one of the following:
- An undergraduate degree in Nursing, Pharmacy, Physiotherapy, Medicine with a minimum of 2nd Class Honours.
- Another healthcare-related undergraduate degree with a minimum of 2nd Class Honours.
- 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 MSc Applied Clinical Data Analytics 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 eligible under the Interim List of Eligible Programmes (ILEP), Ireland's official register of approved educational programs that can accept international students requiring study visas, ensuring programs meet quality standards for immigration purposes.
You can apply online to the University of Galway application portal here. Please review the entry requirements set out in the section above.
You will be required to upload supporting documentation to your application electronically. See the section above on entry requirements for further information on the supporting documentation required for this course.
Closing Dates
For this programme, there is no specific closing date for receipt of applications. Applications will be accepted on a rolling basis and course quotes will be reviewed continuously throughout the application cycle.
Notes
- You will need an active email account to use the website and you'll be guided through the system, step by step, until you complete the online form.
- Browse the FAQ's section for further guidance.
Fees for Academic Year 2025/2026
| Course Type | Year | EU Tuition | Student Contribution | Non-EU Tuition | Levy | Total Fee | Total EU Fee | Total Non-EU Fee |
|---|---|---|---|---|---|---|---|---|
| Masters Full Time | 1 | €9,000 | €23,500 | €140 | €9,140 | €23,640 | ||
| Masters Part Time | 1 | €4,500 | €105 | €4,605 |
For 25/26 entrants, where the course duration is greater than 1 year, there is an inflationary increase approved of 3.4% per annum for continuing years fees.
Postgraduate students in receipt of a SUSI grant – please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2025/26). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.
Note to non-EU students: learn about the 24-month Stayback Visa here.
Postgraduate Excellence Scholarships
This scholarship is valued at €1,500 for EU students applying for full-time taught master's postgraduate courses. You will be eligible if:
- You have been accepted to a full-time taught master's course at University of Galway,
- You have attained a first-class honours (or equivalent) in a Level 8 primary degree.
An application for the scholarship scheme is required (separate to the application for a place on the programme). The application portal for 2025 is now open and available here. Applications will close on the 30th September 2025. Full details available here.
Global Scholarships
University of Galway offers a range of merit-based scholarships to students from a number of countries outside of the EU. Visit here for schemes currently available.
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 1st 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:
Why University of Galway?
World renowned research led university nestled in the vibrant heart of Galway city on Ireland's scenic West Coast.
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Course Introduction
Clinical data analytics for healthcare professionals
The taught postgraduate course in Applied Clinical Data Analytics employs a unique 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 all consist of real-world clinical datasets.
Applied Clinical Data Analytics Handbook 2025
