Data-Science-Class

Repository for all files for the Foundations of Data Science I, II and III course sequence.

Data Science Foundations I: Data Programming

• Intro to functions, arguments, and packages
• Data types and structures
• Basic data input / output
• Logical arguments and groups
• Subsets and merges
• Basic graphs and maps
• Control structures (if-then, loops)
• Regular expressions and strings
• Dashboard project

Data Science Foundations II: Data Wrangling

• Intermediate data types (dates, lists, etc)
• Intermediate data input through APIs (import step)
• Tidy data and tidyverse (tidy cleaning steps)
• Intermediate data wrangling (transform step)
• ggplot (visualize step)
• Applying functions to groups (model step)
• Advanced markdown reporting functions (communicate step)

Data Science Foundations III: Project Management

• Principles of open science and project management (reproducibility)
• GitHub, versioning, and the agile team process
• Documentation of data and files
• Building research databases
• Tufte rules for visualization
• Sharing results through static GitHub pages
• Sharing results through dynamic Shiny apps