Data science relies on working across datasets, teams, disciplines and geographies. Collaboration is crucial, as well as key frameworks. In order to be translatable to patient care, the learning health systems framework helps to conceptualize where healthcare data sits in science, care and evidence domains. Knowledge of key competencies and professions in informatics and data science will facilitate team working. Moreover, without awareness of the national and international datasets which may be available, the “big picture” benefits of data science cannot be achieved.
In this Collaborative Data Science course, you will learn the tools (e.g. phenomics and interoperability and datasets) and guiding principles (e.g. competencies and regulation) to maximize the potential advantages of health data science, whether for patients or policymakers.
You gain insight about the principles of collaborative data science including:
It will also highlight the role and application of collaborative data science:
By the end of the course, you should be able to:
To enroll in this course, you need:
We believe that future-proof research is essential for good care. That is why we combine innovative medical knowledge with didactics. Thanks to our extensive network and proven didactic methods, we make Life Sciences and Health professionals better than yesterday.
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