Data science and AI for COVID-19
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Course Description
This project class investigates and models COVID-19 using tools from data science and machine learning. We will introduce the relevant background for the biology and epidemiology of the COVID-19 virus. Then we will critically examine current models that are used to predict infection rates in the population as well as models used to support various public health interventions (e.g. herd immunity and social distancing). The core of this class will be projects aimed to create tools that can assist in the ongoing global health efforts. Potential projects include data visualization and education platforms, improved modeling and predictions, social network and NLP analysis of the propagation of COVID-19 information, and behavior-nudging tools. The class is aimed toward students with experience in data science and AI, and will include guest lectures by biomedical experts. Prerequisites: background in machine learning and statistics (CS229, STATS216 or equivalent). Some biological background is helpful but not required.
Cross Listed Courses
Grading Basis
RLT - Letter (ABCD/NP)
Min
2
Max
2
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No