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Energy, Climate change, Environment

Introduction to Programming in R course between 19-21 March 2024, Early Bird Prices available until the end of January


Long-time EMODnet Biology partner, the Marine Biological Association is offering a 3-day, online Introduction to Programming in R course, ideal for anyone wanting to use R for data analysis.  Early Bird Discounts are offered for those booking prior to the end of January and there is a free online talk by the course tutor available on their website. 

This course is aimed at anyone wanting to learn how to use R for data analysis.

Requirements: No prior knowledge of the topics covered is required. Participants will need a free account on Posit Cloud. Full setup instructions will be provided prior to the course (see FAQ's for more details).

What is included: Live tutorials during the three days of the course.  Course materials will be available before the course and recordings will be available to you after the course. A certificate of attendance will also be provided.

R is a statistical programming language which has emerged as an important modern data science tool, in academia and beyond. It is open source and freely available, platform independent, extremely powerful for statistical analysis and visualisation and backed by a substantial ecosystem of packages and a large, vibrant community of developers and contributors. The scripted nature of performing analyses in R also contributes to transparency and reproducibility and makes analyses easier to share and easier to build on.

In this course, we’ll start with the basics of working in R as well as introduce basic programming concepts like iteration, writing functions and controlling execution flow. We’ll then dive into using R for data analysis, focusing on what consists of 80% of work involved in analysing data, data wrangling. We’ll focus on using packages in the tidyverse for reading in, manipulating, combining, analysing and plotting data. We’ll also look at literate programming through Quarto, i.e. the process of combining code, text and results of code execution in a single document to produce shareable reports. Throughout all, we’ll also introduce best practices for working with R projects with a focus on reproducibility.

Highlights and Learning Outcomes: 

  • Introduction to basics of R.
  • Programming in R: iteration, controlling execution flow, functions.
  • Data wrangling in R with the tidyverse.
  • Literate programming with Quarto.
  • Best practices in working with R projects.

 Click for the full timetable: MBA | Introduction to programming in R