Episkills: Learn to Code in Python for Epidemiology
Teaching epidemiologists to code
Newly updated for 2020!
This course is for epidemiologists to learn how to write code. Whether you are a complete beginner or you are switching from SAS or R, this course will get you comfortable writing Python to analyze your data. Learning to code will make your data analysis pipeline faster and more reliable, freeing you up to focus on improving the public's health. It will also teach you new ways to think about and interact with your data, making you more effective at uncovering the stories hidden within.
We will cover absolutely everything you need to get started, from installing Python to opening up the software and writing your first line of code. Topics include data cleaning and manipulation; summary and stratified statistics, visualization, and more.
Epidemiology began when John Snow went door to door looking for cholera cases in the 18th century. Public health has made a lot of progress since then, but our methods haven't changed much. We can do better! This course is a resource for epidemiologists to learn programming for data analysis, data management, and data sharing.
Questions? Email me at [email protected]
New for 2020: Did you see there is now a problem set that accompanies this course? See all the options here.
Caitlin Rivers is the author of the package epipy, Python tools for epidemiology. She has a PhD in computational epidemiology and an MPH in infectious disease. She has worked as an epidemiologist in public health practice and is now a university professor.