R Essentials: A Rapid Course for Data Analysis, Visualisation and Communication

Program Overview

Expert instructors guide students through the basics of R, including data handling, statistical analysis, and graphical capabilities. Students also learn advanced skills like writing R functions and using R Markdown to generate reports, enhancing their data analysis capabilities for various applications. The course incorporates Large Language Models to assist with code generation and troubleshooting, providing a practical and engaging learning experience.

Program Outline

Degree Overview:

R is a powerful tool for statistical analysis and data visualisation. R is freely available for the public to use and is a popular tool in all areas of academic scientific research, and also widely throughout the public, and private sector.

Outline:

The course is divided into four days, with each day focusing on a specific aspect of R:

• Day One: Begin with R for Data Analysis:
• Installation process of R
• Using R help
• Preparatory data handling techniques
• Performing simple statistical analysis
• Day Two: Explore (your Data in Colour with) R Graphics:
• Core graphical capabilities of R
• Customising R base graphics
• Features of the ggplot2 package
• Day Three: Develop Advanced R Skills:
• Writing your own R functions
• Advanced statistical analysis
• Day Four: Discover R Markdown:
• Embedding R code into reports
• Customising the layout and style of reports
• Generating reports in various formats

Teaching:

• The course is delivered by:
• Dr Golnaz Shahtahmassebi - Applied statistician
• Dr Ben Dickins - Bioinformatician
• Dr Laurence Shaw - Data scientist
• The instructors adopt a pragmatic approach and embrace the potential of Large Language Models (LLMs) to assist with:
• Code generation
• Code validation
• Understanding error messages
• The full course runs over four days, 10 am to 5 pm each day.

Other:

• Access to desktop computers is provided in a computing suite, but you may also wish to bring your own laptop.
• The practical work and working through examples yourself was great.
This helped me take in the knowledge and allowed for better understanding of the examples.
• Great instruction from brilliant lecturers who were more than happy to impart their knowledge from their diverse fields.
To see the approaches and different ways of using the R product was great. The graphical applications were really useful and something that from a commercial approach could work really well to convince businesses that data has a place in decision making.