Discover data analysis concepts and their applications in healthcare with KCL
Data has had transformative effects on healthcare delivery and management, though many professionals in the sector remain unfamiliar with how to gather and interpret data.
On this six-week course from King’s College London, you’ll explore data science concepts, focusing on how data is collected, analysed, and used to inform professional practice in the healthcare sector.
Examine the data science process, including data modelling, analysis, and visualisation
Data science can help answer questions and explore new perspectives.
You’ll be introduced to data science techniques and systems, defining key terms and concepts, before investigating core skills used in data analysis, modelling, and visualisation.
You’ll also gain an overview of the ethical considerations required when handling data in healthcare, and identify some of the risks and challenges of big data analysis.
With this knowledge, you’ll be able to demonstrate how data can be captured, manipulated, and interpreted for meaningful answers in healthcare contexts.
Work effectively with data scientists and data teams
Having examined the terminology and processes used in data science, you’ll identify opportunities for collaboration with data scientists and teams, improving communication and understanding.
You’ll also be able to explain how your own role may interface with data scientists and data teams.
Understand the role of a data management system in storing and structuring data
You’ll learn how data management systems can organise large amounts of data in an easy to access repository and how this can help optimise data use across departments.
By the end of this course, you’ll have gained an overview of data science processes in healthcare contexts, kickstarting your upskilling in a valuable and necessary area.
This course is designed for healthcare professionals with no experience in data science but whose job roles require them to work alongside or lead teams dealing with data science.
It’s suitable for professionals working in both clinical and non-clinical roles including scientists, management, clinicians, nurses, and pharmacists who have access to and manage data projects or large amounts of data.
