When: 28th November 2018, 9.30 am – 5:00 pm
Where: University of Liverpool, The Foresight Centre 1 Brownlow Street, Liverpool, L69 3GL United Kingdom + Google Map
Who: Dr Dani Arribas-Bel
This is a training and capacity building event organised by the Consumer Data Research Centre (CDRC), an ESRC funded research project of which Jonathan Reynolds is Deputy Director and Co-Investigator.
This course will introduce the participants to the nascent field of Geographic Data Science using the industry standard, the Python programming language. We will cover the key steps involved in solving practical problems with spatial data: design, manipulation, exploration, and modelling. These topics will be explored from a “hands-on” perspective using a modern Python stack (e.g. geopandas, seaborn, scikit-learn, PySAL), and examples from real-world spatial and tabular data.
We will start with an overview of the main ways to access and read spatial data formats such as shapefiles or GeoJSON from disparate sources. Then we will move on to techniques to visualise (e.g. choropleths) and summarise your data, including exploratory spatial data analysis techniques. From there we will cover traditional as well as explicitly spatial unsupervised learning (clustering). The course is intended to provide practical support to researchers and practitioners by introducing them to useful strategies to learn more from their spatial data. There will be time for self-directed learning using data from the CDRC data store.
- Basic understanding of Python as a programming language for data science
- Introductory-level use of the workhorse environment (i.e. Jupyter) and libraries in Python for Data Science
- Visualisation of both spatial and tabular data within Python
- Learn how to perform key GIS operations within the Python (geo-)data eco-system
- Exposure to state-of-the-art work on Integrating modern data science tools and techniques, and more standard GIS functionality
Who is this course suitable for?
The course is intended to provide practical support to researchers and practitioners by introducing them to useful strategies to learn more from their spatial data.
There is no expectation that delegates will have any previous knowledge of Python.
- £60 – UK registered students – register here
- £100 – staff at UK academic institutions & research centres, UK-registered charity & voluntary organisations, staff in public sector & government – register here
- £300 – all other participants including staff from commercial organisations – register here
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Numbers on the course are limited and allocated on a first come, first served basis.