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.
Data Cleaning
Descriptive Statistics
Graphical Exploration
Anomaly Detection
MODULE 2: (6 ECTS CREDITS)
Statistical Inference
This module provides a foundation in statistical inference techniques for biomedical applications. Students will explore probability distributions, hypothesis testing, and confidence intervals within a clinical research context. Topics include parametric and non-parametric methods, ANOVA, Bayesian inference, and likelihood estimation. Through practical applications, students will perform biostatistical analyses on clinical trial and epidemiological datasets, ensuring they can draw valid conclusions from healthcare data.
Probability Distributions
Hypothesis Testing
Confidence Intervals
Bayesian Methods
Regression Techniques
Survival Analysis
Model validation
Feature Selection
MODULE 4: (6 ECTS CREDITS)
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 will explore randomization techniques, endpoint selection, and bias reduction while understanding the biostatistician’s role in study design, sample size estimation, interim analysis, and regulatory reporting. The module covers Statistical Analysis Plans (SAP), interpretation of trial results, and compliance with regulatory standards, ensuring students develop industry-relevant expertise in biostatistical applications in clinical research.
Clinical Trial Phases
Randomization Techniques
Regulatory Guidelines
Statistical Analysis Plans
MODULE 5: (6 ECTS CREDITS)
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. Students will gain hands-on experience with computational resampling techniques using R and Python to enhance their ability to conduct robust statistical analyses.
Resampling Methods
Monte Carlo Simulations
Bayesian Approaches
Hands-on R Programming
Flexible Schedules and Engaging Learning
Flexibility and comprehensive support
Structured schedules
interactive, hands-on learning experiences
Flexible Schedules
Balance live, instructor-led sessions with self-paced content for an adaptable learning experience.
One-to-One Tutorials
Receive individualized guidance to address specific learning objectives or areas of interest.
Project Work
Collaborate on authentic case studies, enhancing teamwork, problem-solving skills, and applied knowledge.
Take part in live Concept Classes to develop advanced skills and strengthen your understanding through practical coding and modeling exercises based on real-world scenarios.
Stay connected with peers and instructors through real-time updates, feedback, and collaborative tools.
Comprehensive Learning Platform
Access recorded live sessions, structured course materials, and supplementary resources at any time.
Our Accreditation
The Data Science Institute is an accredited member of Woolf University, a recognized higher education institution in the European Union. All diploma and degree programs adhere to rigorous European Standards and Guidelines, ensuring international academic excellence and credibility.
ECTS – The Benchmark of Excellence
Our curricula are accredited through the European Credit Transfer and Accumulation System (ECTS), a recognized 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
Recognized by employers, institutions, and government agencies
Opens pathways for further academic progression and supports career development
