Postgraduate Certificate in Data Science (Biostatistics)
A 30 ECTS programme in healthcare data science, clinical research analytics and biostatistics, covering R programming, statistical modelling, clinical trial analysis and epidemiology, and culminating in an applied project. Prepares learners for pharmaceutical, medtech and healthcare roles.
- Credits
- 30 ECTS
- Delivery
- Fully online
- Award
- Postgraduate Certificate in Data Science (Biostatistics)
- Starts
- Monthly
Course Overview
The Postgraduate Certificate in Data Science (Biostatistics Specialisation) is a 30 ECTS programme offering comprehensive training in healthcare data science, clinical research analytics, and biostatistics. Participants build practical skills in R programming, statistical modelling, clinical trial analysis, and epidemiology.
The course includes regulatory compliance and real-world case studies, culminating in an applied project. This programme prepares learners for roles in the pharmaceutical, medtech, and healthcare sectors, and offers a pathway to more advanced or specialised study in data science.
Course modules
Module 1 — Exploratory Data Analysis
This module introduces students to biostatistical data exploration with programming skills. Topics include data cleaning, transformation, and visualisation techniques tailored for biomedical datasets. Students will learn to identify missing values, detect anomalies, and apply summary descriptive statistics in clinical and epidemiological research, with emphasis on graphical representation of health data.
- Data cleaning
- Descriptive statistics
- Graphical exploration
- Anomaly detection
Module 2 — Statistical Inference
This module provides a foundation in statistical inference techniques for biomedical applications. Students explore probability distributions, hypothesis testing, and confidence intervals within a clinical research context, including parametric and non-parametric methods, ANOVA, Bayesian inference and likelihood estimation, applied to clinical trial and epidemiological datasets.
- Probability distributions
- Hypothesis testing
- Confidence intervals
- Bayesian methods
Module 3 — Fundamentals of Predictive Modelling
This module provides a comprehensive overview of regression modelling techniques used in biostatistics and clinical research, including linear regression for continuous outcomes, logistic regression for binary outcomes, and Cox proportional hazards models for survival analysis, applied to biomedical and epidemiological datasets.
- Regression techniques
- Survival analysis
- Model validation
- Feature selection
Module 4 — Clinical Trials and the Role of the Biostatistician
This module covers the fundamental principles of clinical trials, including trial phases, regulatory guidelines, ethical considerations, and Good Clinical Practice. Students explore randomisation techniques, endpoint selection and bias reduction, and the biostatistician's role in study design, sample size estimation, interim analysis, Statistical Analysis Plans (SAP) and regulatory reporting.
- Clinical trial phases
- Randomisation techniques
- Regulatory guidelines
- Statistical Analysis Plans
Module 5 — Resampling and Advanced Methods in Biostatistics
This module covers advanced statistical inference techniques, focusing on resampling methods such as bootstrapping, permutation tests and jackknife techniques. It also introduces Monte Carlo simulations and Bayesian statistical approaches with applications in biomedical research and clinical decision-making, with hands-on computational work in R and Python.
- Resampling methods
- Monte Carlo simulations
- Bayesian approaches
- Hands-on R programming
Ready to start
Apply now, or download the brochure to explore the programme in detail.
Delivery
Fully online, cohort-based, with live teaching and one-to-one support throughout.
Start any month
Monthly starts, no fixed intake. Every student gets an induction at the start covering the platform, the study plan and assessment requirements.
Live classes, recorded
Regular live concept classes with the DSI teaching team, built around practical coding and modelling exercises. Every session is recorded, so you can study around work.
One-to-one tutor support
Individual guidance throughout the programme, with daily live support for questions on material, assessments and progress.
Applied projects
Individual and group work on authentic case studies throughout the programme.
Student community
The DSI Discord channel, where you can raise questions and discuss material with other students and the teaching team.
One platform for everything
Recorded sessions, structured course materials and supplementary resources, available any time.
Internationally accredited
Our accreditation
The Data Science Institute is a full member college of Woolf. Woolf is an accredited, degree-granting Higher Education Institution and is recognised within the European Qualifications Framework (EQF). All diploma and degree programmes adhere to rigorous European Standards and Guidelines, ensuring international academic excellence and credibility.
ECTS
Our curricula are accredited through the European Credit Transfer and Accumulation System (ECTS), a recognised international standard and the world's largest academic accreditation system. ECTS certification ensures widespread acceptance, facilitating both mobility and career development.
Why it matters
Qualifications are internationally portable, recognised by employers, institutions and government agencies, and open pathways for further academic progression and career development.
Admission
The programme welcomes applicants from a range of backgrounds and offers two routes: an academic route for those with a suitable qualification, and a non-academic route for candidates with relevant professional experience.
Academic entry route
For applicants with a suitable academic qualification.
- Honours degree
A 2.2 honours degree (or international equivalent) in a numerate or analytical discipline: Mathematics, Statistics, Computer Science, Engineering, Physics, Sciences, Economics or Business Studies with a quantitative focus.
- Alternative qualifications
Alternative qualifications demonstrating sufficient quantitative or analytical skills are also considered.
Non-academic entry route
For candidates with relevant professional experience or non-degree qualifications.
- Professional experience
At least four years of relevant professional experience, recognised as prior learning (RPL).
- Provisional admission
Join the study track with provisional status under performance-based admission (PBA).
- Full admission
Achieve a GPA of 90% or higher in the first two modules.
- Documents
CV, educational certificates and employer references; supplementary registration fees apply.
English language. IELTS 6.5 or higher, or equivalent, for non-native speakers.
Admissions
Complete the online application form, receive an invitation to enrol, register with Woolf, and finalise your admission through document verification and fee payment. Step one takes about ten minutes. You'll need your qualifications, a CV, and — if you're applying through the non-academic route — employer references.
Online application
Submit your application online with your qualifications and background.
Invitation to enrol
Suitable applicants are invited to enrol on the programme.
Registration
Register with Woolf, DSI's accrediting Higher Education Institution.
Decision
Your application is reviewed and a decision confirmed.
Fee payment
Complete fee payment to secure your place.
Questions
What roles can I pursue after completing the Postgraduate Certificate in Data Science (Biostatistics)?
The programme prepares learners for roles in the pharmaceutical, medtech and healthcare sectors, with practical skills in R programming, statistical modelling, clinical trial analysis and epidemiology.
Does this programme help with upskilling if I'm already in healthcare or life sciences?
Yes. It is built around healthcare data science, clinical research analytics and biostatistics, including regulatory compliance and real-world case studies, so it applies directly to work in healthcare and the life sciences. Every live class is recorded so you can study around work.
How is the Postgraduate Certificate in Data Science (Biostatistics) structured and delivered?
Five modules, 30 ECTS: Exploratory Data Analysis, Statistical Inference, Fundamentals of Predictive Modelling, Clinical Trials and the Role of the Biostatistician, and Resampling and Advanced Methods in Biostatistics. Delivery is fully online, with monthly starts, live teaching and one-to-one tutor support throughout.
When do live online classes take place, and what support is available?
Live concept classes with the DSI teaching team run regularly throughout the programme, and every session is recorded so you can study around work. Support comes from one-to-one tutors, daily live support for questions on material, assessments and progress, and the DSI Discord channel, where you can reach other students and the teaching team.
What kind of assessments or projects are involved?
Applied work throughout, including individual and group work on real-world case studies, culminating in an applied project. The assessment requirements are covered at your induction.
Is the Postgraduate Certificate in Data Science (Biostatistics) accredited or recognised?
The Data Science Institute is a full member college of Woolf, an accredited degree-granting higher education institution recognised within the European Qualifications Framework. The programme carries 30 ECTS credits at EQF Level 7.
Can these credits be applied toward advanced study?
Yes. The certificate offers a pathway to more advanced or specialised study in data science. ECTS is the European standard for credit transfer; recognition by another institution is at that institution’s discretion.
What academic qualifications do I need?
A 2.2 honours degree, or international equivalent, in a numerate or analytical discipline such as Mathematics, Statistics, Computer Science, Engineering, Physics or the Sciences, or Economics or Business Studies with a quantitative focus. Alternative qualifications demonstrating sufficient quantitative or analytical skills are also considered.
Can I still apply if I don't meet the minimum degree requirement?
Yes, through the non-academic entry route. It requires at least four years of relevant professional experience, recognised as prior learning. You join with provisional status and move to full admission by achieving a GPA of 90% or higher in the first two modules. Alternative qualifications demonstrating sufficient quantitative or analytical skills are also considered on the academic route.
What about English language requirements?
English language skills equivalent to IELTS 6.5 or higher are required for non-native speakers.
How do I apply for the programme?
Complete the online application form, which takes about ten minutes. Suitable applicants are invited to enrol, register with Woolf, DSI’s accrediting higher education institution, and secure their place through document verification and fee payment.
Is this programme recognised in Ireland?
The Postgraduate Certificate in Data Science (Biostatistics) is awarded through Woolf, a Higher Education Institution licensed by the Malta Further and Higher Education Authority (licence 2019-015), and carries 30 ECTS credits at EQF Level 7. NARIC Ireland, the Irish ENIC-NARIC centre at QQI, advises that a Maltese postgraduate certificate is comparable to an award at NFQ Level 9. The programme is not validated by QQI. Full details are on the Accreditation page.
Where can I find more information or help?
Email info@datascienceinstitute.net or call +353 21 204 0519.
Apply for the Postgraduate Certificate in Data Science (Biostatistics)
Applications are reviewed on a rolling basis with monthly starts. If you'd rather talk it through first, an admissions advisor can call you.