Introduction to Geographic Data Science
Classes
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Overview
This is a credit bearing course but can also be taken as a non-credit bearing course.
Discover the difference between our credit bearing and non-credit bearing courses.
This Introduction to Geographic Data Science short course introduces you to the newly emerging subject of geographic data science. It first explores how to digitalise and map events and phenomena that happen in the real world using Geographic Information Systems (GIS) - a computer system for handling spatially referenced data. We will then identify different types of spatial data and discuss how they can be used in solving a wide range of problems using geoprocessing methods. Examples range from facility locations (e.g. finding the best location for an urban/retail facility solving multiple spatial and non-spatial conditions) to environmental issues (e.g. mapping and estimating damages by pollution and natural disasters) and more. Finally, by working on various case studies, you will gain hands-on experience in capturing, editing, mapping, analysing, sharing and presenting spatial data, essential skillsets for independently solving data science problems.
The second part of the module focuses on Big Data management and modern geospatial data formats. You will learn how to work with different data types in GIS software and how to represent these data on a geospatial database. In addition, you will be introduced to the concept of relational databases, entity-relationship modelling, and spatial databases suitable for representing geographical data.
Each lecture will be accompanied by a practical session designed around specific real-world applications (including but not limited to urban, social, environment, retail, health and diseases) to help acquire practical techniques for data handling and solving geographical problems under various settings.
We plan to cover the following content:
- What is geospatial data?
- Representing geography in a digital form
- Digital map production
- Spatial data models
- Vector- and raster-based geoprocessing analysis and spatial queries
- Georeferencing and coordinate systems
- Working with modern geospatial data formats - Big Data
- Relational databases and Structured Query Language (SQL)
- Spatial databases
- Geospatial applications examples
Introduction to Geographic Data Science is a postgraduate-level short course and is ideal for data analysts who wish to expand their expertise through acquiring knowledge and skills in geospatial science. It will also suit professionals who are considering a postgraduate education in geographic data science and wish to take a taster module to see if it matches their interests/career plans.
Assessment for this course is via two pieces of practical coursework: (a) construction of maps and a simple analysis of 3000 words (50%), and (b) collection and handling data from different sources and analysing it using different spatial tools (50%).
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Entry requirements
Entry requirements
As this is a postgraduate-level course, you will need to have already gained a second-class honours degree (2:2) or above in a related discipline though other fields will be considered. You will also need to be proficient in standard computer packages (for example, word processing, spreadsheets) with an interest in using GDS software. Effective oral and written communication skills in English are essential.
As part of the enrolment process, you may be required to submit a copy of a suitable form of ID.
International students who wish to come to the UK to study a short course can apply for a Visitor visa. Please note that it is not possible to obtain a Student visa to study a short course.
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How to apply
How to apply
You register directly onto the classes you would like to take. Classes are filled on a first-come, first-served basis - so apply early. If you wish to take more than one short course, you can select each one separately and then register onto them together via our online application portal. There is usually no formal selection process, although some modules may have prerequisites and/or other requirements, which will be specified where relevant.