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:

• Best Practices for Scientific Computing
• Good enough practices in scientific computing

Mon 5/22
	IRB and Ethics Training:	Sallie Keller, Gizem Korkmaz
	System Setup: Git Bash Server Access RStudio Connection Database Connection	Aaron Schroeder / Daniel Chen
	Unix Tools: Navigating Directories & Working with Files (cd, ls, mkdir, touch, nano) Shell Scripts (running shell scripts and understanding the working directory) SSH (connecting to a remote server/computer with secure shell)	Daniel Chen
Tue 5/23
	Git Setting up Git Creating a repository Tracking changes Exploring history Ignoring Things Remotes in Github Collaboration Conflicts	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 Files (csv, Excel, RData, zip) RCUrl (ftp, ftps, sftp) JSON APIs (Google Dev, Arlington, googlesheets) Database (SQL, DBI/PostgreSQL)	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
	Knitr/RMarkdown Basics Conditional Subsetting Dataframes Missing Values	Daniel Chen
	Training: SQL, SQL, SQL!!! - What is SQL and why? R and SQL Selecting data Insert data Combining (Joining) Sorting and removing duplicates; Filtering; Aggregation	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