A. Knowledge and understanding
- Reproduce basic concepts in Epidemiology
- Efficiently read and interpret scientific articles
B. Applying knowledge and understanding
- Develop, improve or extent on a data science solution in the healthcare sector, while keeping complex and/or extensive practical requirements that apply into account.
C. Making judgements
- Approach your solution with curiosity, creativity, and in an analytical manner, incorporating the needs of patients, health care professionals, and other stakeholders.
- Ability to translate the proposed solution to laymen stakeholders in the healthcare sector
“Health analytics” is a rapidly growing domain of data science. In a world where data is boss, a sensor can solve any problem, and every organization seems eager to let AI decide important matters, it is important that you not only understand how to run analyses, but also how the human factor and unconscious biases may impact your data or decision. Lastly, in your future career you also need to be able to convey your message back to people in the healthcare sector who do not have the same background as you.
In this course, we will focus on key concepts in health analytics and epidemiology. We will discuss the application of these concepts in research and their impact public health and society.
For example, we will explore how data collection is often limited by observational biases. Observational biases typically influence the outcome of an analysis and thus results. Understanding of epidemiological concepts is therefore crucial for the interpretation of results, especially in context of large amounts of health data.
The course will put emphasis on theory, ideas, and their translation back to a business environment. I will attempt to invite practitioners working in the field of health analytics to discuss applications in different medical contexts.
Students are expected to participate actively in the practical sessions by means of working on assignments and presentations. Low participation rates will result in a lower grade for your group assignment and presentation.
- Individual final exam: 60% of your grade
- Group assignment: 30% of your grade
- Presentations: 10% of your grade