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.