In a digital-first healthcare environment, the ability to confidently manage, clean, and analyse health data is essential. The Computer Programming for Health Research module provides a practical foundation in core programming tools used by data scientists across the health sector. You will build skills in SQL for querying databases, Python for advanced data cleaning and analysis, R for statistical processing and visualisation, and Git for version control and reproducible research.
Delivered through a combination of lectures, hands-on coding sessions, and real-world case studies, the module equips you to handle the full data pipeline—from accessing and managing data in relational databases, through to preprocessing, analysis, and communication of results. You will develop programming skills to tackle tasks like resolving missing values, managing duplicates, and transforming datasets, using efficient algorithms and custom functions—all using industry-standard tools and packages.
By the end of the module, you will have developed fluency in key programming languages and techniques that underpin modern health data science workflows, with practical experience in collaborative coding and structured project management.
Assessment is 100% coursework-based and grounded in authentic health data science tasks. Assessment 1 (50%) involves using SQL to extract and summarise data from a simulated clinical database. Assessment 2 (50%) challenges students to write Python code for preprocessing and analysing a health dataset. Each includes written reports and supporting code, mirroring the expectations of professional data science practice.
Whether you are preparing for a role in health analytics, biomedical research, or data-driven healthcare innovation, this module delivers the hands-on technical foundation you need to succeed.