Data Science for Operational Researchers Using R

Improve your personal productivity for generating rapid and insightful results from large data sets using R.

Description

Learn about the role of R in the overall data science life process whilst appreciating the power of R and the 'tidyverse' set of packages for increasing productivity.

Learning objectives

  • How to install, configure and use RStudio 
  • Understand key R data structures 
  • How to write a function in R, and how to use and apply a family of functions 
  • Explore data visually using ggplot2 
  • How to filter and join data 
  • Apply all the R technical elements to an operational research-based case study. 

Topics

  • Foundations of the R Language: Vectors, Lists, Data Frames and Functions 
  • An overview of Exploratory Data Analysis 
  • The ggplot2 package for visualising data 
  • The dplyr package for summarising and analysing data 
  • The tidyr package for preparing data, and R markdown for communicating results 
  • R for operational researchers: analysing simulation output from sensitivity runs. 

Audience

The course will benefit operational research practitioners who support data-driven decision-making within their organisation and are interested in exploring new tools, workflows and methods to generate insights and communicate them to stakeholders. 

Course format

  • Powerpoint presentation to introduce the topics 
  • Case studies based on ‘real world’ problems 
  • R Studio Cloud (available online) 
  • Group discussion/work 
  • Bring questions from your own work to embed your learning 
  • Follow up on the course with online resources, case studies and solutions. 
  • Option to connect with the R open-source community and its many resources for supporting data analytics and the process of converting information into action. 

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