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This is a free, self-paced online course.
Using COVID-19 as a case study, this project provides a GIS analytics platform for the COVID-19 impact and scenario planning in the following subject areas:- rental and mortgage affordability, remote accessibility, vulnerable cohorts, social economic impact and sentiment analysis related to different Local Government Areas (LGAs).
At the beginning of this taster course, participants are introduced to the project and the problem. The solution is subsequently explored using a case study format. Information about the solution is provided, whilst being cognisant of the considerable impact of COVID-19.
Participants are asked to consider how the skills and knowledge used in the project may be transferred into their industry or role and how the solution could be applied to other real-world problems they might encounter in their field of work.
The project will provide the GIS analytics platform for COVID-19 impact and scenario planning, inputting a range of data related to different LGAs. The data is presented visually on an online platform, with an interactive function for participants to engage with.
The solution is data driven, based on recommendations from SMEs in areas such as:
The solution will provide up-to-date, granular data, that enables users to make time-critical decisions about responses during the COVID-19 outbreak.
This case study will provide an opportunity for participants to engage with the following learning outcomes:
This taster course is suitable for anyone who is interested in Covid-19 impacts in NSW and tools that can enable scenario planning.
START DATE |
Start anytime |
MODE |
Online |
DURATION |
Self paced |
Learn the power and language of data analysis and get hands-on with key techniques for mining and analysing data.
Go in-depth into key Machine Learning concepts through theory, maths and programming.
Build your foundational data background to develop a skillset to run data mining and analysis projects.
Explore tools to analyse and present data on NSW communities during the early to mid-stages of COVID-19.
Understand the global response to COVID-19 through a data-driven approach, to explain how nations have responded.
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