Training and Events
R for Transport Applications: Handling Big Data in a Spatial World
|University of Leeds|
Dr Robin Lovelace
26/04/2018 - 27/04/2018
Level 11, Worsley Building, University of Leeds
View in Google Maps (LS2 9NL)
This 2 day course teaches two skill-sets that are fundamental in modern transport research: programming and data analytics, with a focus on spatial data. Combining these enables powerful transport planning and analysis workflows for tackling a wide range of problems, including:
This course will provide tools, example code and data and above all face-to-face teaching to empower participants with new software to answer these questions and more. The focus is on the programming language R (we will briefly look at visualising results in QGIS). However, the principles and skills learned will be cross-transferable to other languages. By providing strong foundations in spatial data handling and the use of an up-coming language for statistical computing, R for Transport Applications aims to open a world of possibilities for generating insight from your transport datasets for researchers in the public sector, academia and industry alike.
As with any language, it is important to gain a strong understanding of the underlying syntax and structure before moving on to complex uses. This course therefore starts with the foundations: how R can be used to load, manipulate, process, transform and visualise spatial data.
In terms of content, the first day will focus on how the R language works, general concepts in efficient R programming, and spatial and non-spatial data classes in R. Building on this strong foundation the second day will cover the application of the skills developed in Day 1 to transport datasets, with a focus on geographical transport data.
Intermediate (some prior knowledge)
Early bird prices (valid until 27 March)
Website and registration
Yorkshire and Humberside
Quantitative Data Handling and Data Analysis, ICT and Software
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