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Data Science in Health Care


Admission requirements

Required course(s):



Health data science is an interdisciplinary field that applies data science methods and techniques to address health-related problems and improve health outcomes. It is a rapidly growing and exciting area that has applications in various domains such as public health, clinical care, biomedical research, health policy, and health education. Health data science helps us better understand diseases and health conditions, identify people at the highest risk of illness, and formulate policies on the best ways to provide care and treatment.

In this course, we will learn the fundamentals of health data science, including the data science roadmap, the theoretical background, and the basic skills to use some programming tools such as Python and R. We will also learn how to recognize the different types of health data, how to articulate a coherent and complete research question, how to design and interpret queries, and how to communicate your findings effectively. No previous experience in programming is required for this course. Students will be taught step by step how to use programming for health data science from the very beginning. This course will equip students with the knowledge and skills to use health data science for solving real-world problems with health data and creating value for health systems.

Course Objectives

By the end of this course, students will be able to:


  • Demonstrate an understanding of key terminology and concepts related to health data science, such as data types, data sources, data analysis, data visualization, and data ethics.

  • Demonstrate an understanding of how to apply health data science methods and techniques to solve real-world problems with health data.


  • Develop and carry out a scientifically sound health data project, from defining a research question and collecting data, to performing data analysis and reporting results.

  • Effectively demonstrate scientific and technical skills related to health data science topics, such as data cleaning, data exploration, data modeling, and data communication.

  • Effectively demonstrate critical thinking and problem-solving skills related to health data science topics


Timetables for courses offered at Leiden University College in 2023-2024 will be published on this page of the e-Prospectus.

Mode of instruction

This course focuses on both theoretical ideas underpinning how health data science works and the practical skills you will need to use health data science. To this end, this course will rely on in-person lectures in classrooms to introduce concepts and skills and then students will be asked to apply lecture material through hands-on exercises, assignments, and projects.

Assessment Method

  • Participation in class, 10%

  • Three assignments (15% each), 45%

  • Final exam, 15%

  • Final project, 30%

Reading list

Literature and reading materials will be announced during the course.


Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator,


Dr. Joy Lee,


It is assumed that students have no previous computer programming experience.