Applied Clinical Data Analytics (MSc)

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.

Applications and Selections

• The applicant will submit their output through an online portal. Launch-date of that portal will be listed herre.

• Course applications are then made online via the University of Galway Postgraduate Applications System.

Who Teaches this Course

• Dr Conor Judge, School of Medicine
• Professor Martin O’Donnell, School of Medicine
• Professor Andrew Smyth, School of Medicine
• Dr Catriona Reddin, School of Medicine

Sonja Khan

B.Sc.,M.Sc, PhD

Lecturer Above The Bar
School of Medicine
NUI Galway
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Dr John Ferguson

B.A.,M.Sc.,PhD

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Dr Alberto Alvarez-Iglesias

B.Sc., M.Sc., Ph.D.

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Requirements and Assessment

Assessment is via a combination of continuous assignments (70%) and written exams (30%), that will be 100% computer-based assessment.

Key Facts

Entry Requirements

Additional Requirements

Recognition of Prior Learning (RPL)

Course Outline

University of Galway have launched a graduate course in Applied Clinical Data Analytics that employs a unique and innovative spiral curriculum, designed specifically for training healthcare professionals in analysis of clinical data.

The programme will be delivered by domain experts in Clinical Data Analytics from primarily within the School of Medicine and wider College of Medicine, Nursing and Health Science. Working within a dynamic active learning environment on clinical data will facilitate the development of profession appropriate, individual, collective and inter-professional data skills. Assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.

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 applied and students will learn by applying statistical tools to work through data sets.

Research project:
Self-directed research project with continuous supervision and feedback.

Figure 2—Term Overview for MSc Applied Clinical Data Analytics (part-time)

Why Choose This Course?

Career Opportunities

Who’s Suited to This Course

Learning Outcomes

Transferable Skills Employers Value

Work Placement

Study Abroad

Related Student Organisations

Course Fees

Fees: EU

Fees: Tuition

Fees: Student levy

Fees: Non EU

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