Introduction to R

The first part of this course teaches R with a focus on manipulating and visualizing data. You will get set up with a functional RStudio workflow, learn to use different file types, transform data tables, import and manipulate data, use functions and loops, create data visualizations, make a Shiny app, and learn how to solve problems with their programming. Both base R and tidyverse methods are included. To work reproducibly, you will create R Projects.

The second part of the course will cover the ethics of consent, Equity, Diversity & Inclusion (EDI) training, and professional skills including presentation, project management, and data security. Finally, the course will conclude with an industry case study.

Requirements

This course is designed for those who have a degree in something other than Computer Science/Statistics and are looking to enhance their data science skills for their career.

Learning Outcomes

The ability to set up and use R and RStudio
The ability to manipulate and visualize data
The ability to fix errors
An understanding of consent in data-based studies
The ability to make presentations and manage projects

Delivery Format/Length

Online for 7 hours/week for 3 weeks (21 hours in total).

2022 Dates

Monday 7 November, 6pm-8pm: Hello World! And Work practices (R basics; file types; errors)
Thursday 10 November, 6pm-8pm: Data in R (Key data types: tibbles, strings, factors, times, missing values)
Saturday 12 November, 9am-noon: Manipulation I (Filtering; arranging; selecting; mutating)
Monday 14 November, 6pm-8pm: Manipulation II (The pipe; grouping; summarizing)
Thursday 17 November, 6pm-8pm: Wrangling I (Importing data; database in R; cleaning)
Saturday 19 November, 9am-noon: Wrangling II (Pivot; joining data; data.table)
Monday 21 November, 6pm-8pm: Programming (custom functions); visualization; shiny; ethics; inequity
Thursday 24 November, 6pm-8pm: Professional skills: Industry case study
Saturday 26 November, 9am-noon: R: Review and Practice