Schedule & Lesson Material for the Data Science for the Public Good Program at the Social and Decision Analytics Laboratory.
The Data Science for the Public Good program teaches student fellows how to sift through vast amounts of information related to public safety, employment, and the provision of services to discover how communities can become more efficient and sustainable. Through the lenses of statistics, social science, and data science research, DSPG students will learn to integrate all available data resources
Why things are setup the way they are:
| Mon 5/22 | ||
|---|---|---|
| IRB and Ethics Training: | Sallie Keller, Gizem Korkmaz | |
System Setup:
| Aaron Schroeder / Daniel Chen | |
Unix Tools:
| Daniel Chen | |
| Tue 5/23 | ||
Git
| Daniel Chen | |
| Git Pull Request Collaboration | Daniel Chen | |
| Wed 5/24 | ||
| Servers and code repositories | Daniel Chen | |
| Project Setup & Templates | Daniel Chen | |
Data Ingestion & Storage
| Daniel Chen | |
| Thu 5/25 | ||
| Code repositories, project templates, and where to put and access your data | Daniel Chen | |
| Data Objects in R: Data.Frames | Daniel Chen | |
| Functions and apply & Looping in R 'for' loops vs apply family | Daniel Chen | |
| Fri 5/26 | ||
| Daniel Chen | |
Training: SQL, SQL, SQL!!! - What is SQL and why?
| Aaron Schroeder | |
| Tue 5/30 | ||
| Group by statments | Daniel Chen | |
| Making Choices & Modeling in R | Daniel Chen | |
| Loops | Daniel Chen | |
| Reshaping data / tidy data | Daniel Chen | |
| Regular Expressions | Daniel Chen | |
| Wed 5/31 | ||
| ACS | Vicki Lancaster | |
| Thu 6/1 | ||
| The Data Science Process & Data Discovery | Aaron Schroeder | |
| Data Structure Profiling: Missing Variables, Combined Variables, Multiple Observation Directions, Combined Observational Unit Types, Divided Observation Unit Type | Aaron Schroeder | |
| Data Quality Profiling: Completeness, Value Validity, Consistency, Uniqueness, Duplication | Aaron Schroeder | |
| Plotting | Daniel Chen | |
| Fri 6/2 | ||
| data.table | Daniel Chen | |
| Working directories | Daniel Chen | |
| Running R scripts | Daniel Chen | |
| Background and detach processes | Daniel Chen | |
| Mon 6/5 | ||
| Training: Web Scraping | ||
| Training: Data Presentation & Reporting (Shiny, Markdown/Latex, knitr) | Daniel Chen | |
| Wed 6/7 | ||
| "Machine Learning" whirlwind | Daniel Chen | |
| Fri 6/9 | ||
| Data Vizualization & Exploration in R | Josh Goldstein | |
| Secure & Federated Record Linkage | Aaron Schroeder | |
| Training: Working with Geographic Data in R | Aaron Schroeder | |
| Spatial Data Objects in R: Spatial Data.Frames [point, line, polygon], Rasters | Aaron Schroeder | |
| Mapping Food Deserts: A Shiny Dashboard | Aaron Schroeder | |
| Training: Machine Learning in R | Daniel Chen | |
| Training: Baysian Analysis in R | Dave Higdon | |
| Wed 6/14 | ||
| Training: Agent-Based Modeling with NetLogo | Bianica Pires | |
| Agent-Based Modeling Approaches | Mark Orr | |
| Wed 6/21 | ||
| Social Network Analysis | Gizem Korkmaz | |
| Thu 7/27 | POSTER SESSION!! | |
| Speakers: Nancy Potok and David Yokum | ||