This learning research community is a 10-week series of technical lectures and workshops to introduce health disparity researchers to data science through practical, hands-on training. Lectures will introduce fundamental principles and techniques of data science in order to extract useful information and knowledge from data. In parallel to lectures, workshop participants will also learn how to explore data, define cohorts and build participant-level datasets using the All of Us Researcher Workbench. Participants will also learn how to write reproducible and modular code with R, including programming best practices.
Dates: September 6th – November 15th, 2022
Registration: Link to WAITLIST (DUE TO AN OVERWHELMING RESPONSE, WORKSHOP REGISTRATION HAS BEEN CLOSED. WE WILL LET EVERYONE KNOW WHEN THE REGISTRATION RE-OPENS).
|1||Introduction to data science and health disparities seminar||Intro to R and RStudio|
|2||Minority Health and Health Disparities||Project Management with RStudio / Seeking Help / Writing Good Software|
|3||Introduction to Classification||Data Structures|
|4||Evaluating Classifier Performance||Exploring Data Frames / Subsetting Data|
|5||Using Proximity to Make Predictions||Control Flow / Functions Explained|
|6||Interrogating Assumptions||Creating Publications - Quality Graphics with ggplot2|
|7||Introduction to Clustering||Splitting and Combining Data Frames with plyr|
|8||Analyzing Unstructured Text||Data Frame Manipulation with plyr|
|9||Introduction to Deep Learning||Data Frame Manipulation with plyr|
|10||Case Study: Topic TBD||Producing Reports with knitr|