This course gives the essential knowledge to get started with a data science project in R using the Tidyverse package. We will learn to tell stories with data using the scientific data analysis workflow and analytic tools based on the R system.
Learners will be able to use the Tidyverse to automate tasks efficiently. They will learn how to use best practice techniques in their workflow from data ingestion through to communication of results.
- Understand the scientific approach to the data analysis workflow and why and how R contributes to the process;
- Be able to import data into R in different text formats, flat files, excel, SAS, STATA and SPSS files as well as data from the web;
- Know the concept of tidy data, identify messy features in a data set and tidy it ready for analysis;
- Use simple exploratory analysis, including visualisation, to understand the data structure and some information it contains and also to detect, be aware of, and possibly correct, data anomalies;
- Be able to create a basic report of data analysis using a R notebook;
- Work with the Tidyverse packages readr, tidyr, dplyr, stringr, ggplot2, forcats, lubridate, etc.
E learning – Available
Self learning – Not available
Face to face – Not available
Beginner. Familiar with basic R syntax.
To discuss booking this course for remote delivery, please contact the Data Science Campus Faculty.