The Library’s Research Data Services will be offering 1-credit short courses again this spring in partnership with the Data Science Institute: Data Wrangling in R and Applied Causal Inference. The graduate-level short courses meet for 5 weeks, and are designed to provide some focused, hands-on training on different topics and tools; researchers from any discipline are welcome to join in the fun. DSI is also partnering with the School of Architecture to open the 3-credit Data Visualization course to a broader audience.
DS 6559-001 Data Wrangling in R (1 credit, meets the first five weeks of the semester)
T,R 12:30-1:45 from 1/21/2016-2/23/2016
New Cabell Hall 303
This course covers data cleaning and data manipulation in R. Topics include reading in/writing out data in various formats, R data structures, working with date/time data, character manipulation, using regular expressions in R, reshaping data, data transformations, data aggregation and basic data visualization to aid in data cleaning.
DS 6559-002 Applied Causal Inference (1 credit, meets the second five weeks of the semester)
T,R 12:30-1:45 from 2/25/2016-4/5/2016
New Cabell Hall 303
This course examines approaches to causal inference using the potential outcomes framework. Methods covered will include matching, difference-in-difference, regression discontinuity, and instrumental variables, . The course will be a mix of lectures, discussion, and application examples in R and will emphasize understanding the approaches conceptually and implementing them computationally.
SARC 5400-001 Data Visualization
This is a course about information and data visualization. We live in a world rich with information. This course teaches visual and spatial thinking coupled with data analysis tools and custom web-enabled programming to construct and envision information. To find and even invent approaches toward seeing into complex problems, we will study, and make, useful, compelling and beautiful tools to see.