Data science is a multidisciplinary field that brings together domain knowledge with expertise from mathematics, statistics, computer science, engineering, and epidemiology. By combining scientific methods and analytical techniques, it helps transform large amounts of structured and unstructured data into meaningful insights. In health research, rapid technological developments have led to an enormous increase in the availability of health-related data, offering new possibilities for research and innovation.  

This course is a foundational introduction to the world of data science core concepts in health research and explains their relevance for health-related questions. 

Rather than diving straight into complex coding, we focus on the "why" and "how" behind the methods, giving you a clear roadmap of the landscape. 

Objectives

• Understand that epidemiology is at the core of data science in healthcare; 

• Understand the core concepts and terminology of data science relevant to health research. 

• Discuss how different types of health data can contribute to answering research questions. 

• Evaluate the opportunities and challenges of applying data science methods, including machine learning, in health research. 

Participant profile

Clinical researchers, clinical epidemiologists, computer scientists, those in health technology assessment or value-based healthcare. 

Assessment