Fundamentals of Data Science in R

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Efficiently manipulate and wrangle data using appropriate tools, including the dyplr R package
• Understand the importance and power of effective data visualisation and be able to produce sophisticated graphics, for example using the ggplot2 R package
• Understand the ethical considerations of data collection, management and use
• Develop interactive tools for data exploration using Shiny
• Manage data-based and statistical projects using tools for reproducibility and version control

• Goals of data science and different data types
• Reproducible workflows and reports using Quarto
• Version control using Git
• Data manipulation and wrangling
• Data visualisation
• Interactive data exploration
• Data ethics and repeatability, replicability and reproducibility
• Additional topics, that may include challenges of big data, an introduction to distributed computing or text data and web scraping

12 Lectures

24 Computer labs

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.