Empowering the Public Sector: Delving into Data Analytics
Archived – Please note this training opportunity/webinar took place in the past and has been left here for reference purposes. You can look for similar training opportunities/webinars by viewing our full list here or by sending us an . Where they are available you will find video recordings from this training below.
The Business and Local Government Data Research Centre (BLGDRC), and the Catalyst Project, both based at the University of Essex, are working in conjunction to deliver several data analytics training sessions, aimed at the public sector.
The course delivered in January will consist of three separate training sessions. Attendees are able to attend all three sessions or choose the session which they feel is most relevant to their needs.
The series takes place on Thursday 12 January (all day) and Friday 13 January (morning only). You can register for the whole series or view the individual sessions below and register for those which are most relevant to you.
An Overview of Agent Based Modelling
Date: Thursday 12 January
Time: 10am – 12.45pm (9.30am registration)
Location: PC Lab M, Colchester Campus, University of Essex
Watch the recording from this session below or click here:
Agent Based Modelling (ABM) is a computational modelling approach in which we build simulations of social and policy processes in an attempt to understand better those processes.
ABM has been used by researchers, Professor Vania Sena and Professor Abdel Salhi, from the Business and Local Government Data Research Centre to produce a simulation model to understand the drivers of growth on the High Street of Colchester. This is just one of many ways that ABM can be used to assist the public sector.
In this session Dr Peter Barbrook-Johnson, from the Policy Studies Institute at the University of Westminster, will provide attendees with a basic understanding of agent based modelling, and then allow attendees to explore the NetLogo modelling software for themselves with several short exercises, to enable them to begin putting their knowledge into practice.
Attendees will then be given the opportunity to network, with lunch provided.
No prior knowledge is required.
Predictive modelling: shifting from reaction to prevention
Date: Thursday 12 January
Time: 1.45pm – 4.30pm
Location: EBS.1.1, Colchester Campus, University of Essex
Unfortunately a video recording from this session is not available.
A seminar by Dr Aris Perperoglou, University of Essex
In a climate of public sector resource and funding austerity, funds need to be invested in activities that add value and improve public sector services. This seminar will explain how Predictive Modelling can be used to understand hidden mechanisms and underlying patterns in historical and current data, with the aim of successfully predicting future outcomes so that opportunities for early interventions can be identified, and the use of scarce resources optimised.
Data linkage techniques (GIS)
Date: Friday 13 January
Time: 10am – 12.45pm (9.30am registration)
Location: PC Lab M, Colchester Campus, University of Essex
Watch the recording from this session below or click here:
Andrew Lovett is Professor of Geography at the School of Environmental Sciences at the University of East Anglia, and a researcher for the Business and Local Government Data Research Centre. Since 1990 Andrew has been involved in a range of projects concerned with applications of geographic information systems (GIS), landscape visualisation software and statistical techniques.
In this workshop Andrew Lovett will give attendees a brief understanding of GIS and the data linkage techniques that can be used to integrate information from different sources to help address policy questions. The workshop will consist of an introductory talk and a series of practical exercises (using the ArcGIS software) that will allow attendees to put their acquired skills into practice. Attendees will then be able to participate in a closing Q&A session.
Attendees will be given the opportunity to network afterwards, with lunch provided.