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ALLSTAT  January 2019

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Subject:

TRAINING: Short Courses from the Consumer Data Research Centre (Leeds)

From:

Kylie Norman <[log in to unmask]>

Reply-To:

Kylie Norman <[log in to unmask]>

Date:

Wed, 2 Jan 2019 14:59:00 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (214 lines)

Dear Colleagues,



**With apologies for cross-posting**



The ESRC-funded Consumer Data Research Centre<https://www.cdrc.ac.uk/> at the University of Leeds is currently offering the following courses in 2019:






Spatial Modelling for Retail Analytics<https://www.cdrc.ac.uk/events/spatial-modelling-for-retail-analytics/> - still some places left

28th Jan 2019 @ 9:30 am - 4:30 pm

Leeds Institute for Data Analytics, University of Leeds

Course Tutors: Drs Andy Newing and Nick Hood

This one-day course introduces participants to sophisticated spatial analysis and spatial modelling approaches that can be used to understand retail sector dynamics. We focus on the analysis of complex interactions between retail demand (consumers) and the retail supply side (retail stores). The tools that we introduce are applied widely by the commercial retail sector and we reflect on the important link between academia and industry in the continual development of these modelling approaches. We introduce participants to statistical and spatial modelling using simulated data related to UK consumers. These include regression and powerful industry-standard spatial interaction (or gravity) modelling. The course is taught via a series of fully supported hands-on practical sessions, interspersed with short lectures and group activities. This provides an applied and theoretical perspective, with examples drawn from the UK but relevant in a number of international contexts.

Who is the course suitable for? This course is designed for participants who have some experience of spatial analysis using GIS, but no prior knowledge of statistical or spatial modelling is required. Participants are likely to be PhD students or researchers looking to use spatial modelling to enhance their analysis of retail/consumer data in. The course will signpost participants towards CDRC and freely available data resources which would enable them to extend these analysis in their subsequent work.



Cost:

70 (students)

120 (academic, public and charitable sector employees)

300 (private sector)



Introduction to ArcGIS<https://www.cdrc.ac.uk/events/introduction-to-arcgis/>

15th Feb 2019 @ 9:30 am - 4:30 pm

Leeds Institute for Data Analytics, University of Leeds

Course Tutor: Rachel Oldroyd

Due to licensing restrictions, we regret that this course is only available to people registered or employed at a UK Higher Education Institution

This 1 day course provides an introduction to Geographical Information Systems (GIS) using ESRI's ArcGIS version 10.2 software. It provides participants with the opportunity to familiarise themselves with using and navigating the software, as well as focusing on the skills of data entry, data manipulation, editing, analysis and mapping. The emphasis of this course is working with vector data in the context of a variety of socio-economic applications. The course will mix teaching with demonstrations and hands-on exercises.

Objectives
         To introduce new users of Geographical Information Systems to ESRI's ArcGIS v10.2
         To provide skills in data entry, data manipulation, spatial analysis and thematic mapping
         To encourage participants to reflect on how the mapping and basic spatial analysis techniques might be used in their own research area.

Cost:

70 (students)

120 (academic, public and charitable sector employees)



Spatial Analytics for Public Health Researchers<https://www.cdrc.ac.uk/events/spatial-analytics-for-public-health-researchers/>

6th March 2019 @ 9:30 am - 4:30 pm

Leeds Institute for Data Analytics, University of Leeds

Course Tutor: Michelle Morris

This 1 day course offers an introduction to spatial analytics in a public health context. As spatial data sets get larger, more sophisticated software needs to be harnessed for their analysis. R is now a widely used open source software platform for statistical analysis and is increasingly popular for those working with spatial data thanks to its powerful analysis and visualisation packages. This course introduces the basics of how R can be used for spatial data. The course will begin with an overview of different spatial units and how they fit together. Public health examples will be used to illustrate the relevance of using each of these units. You will work through examples of how spatial units can be added into existing data sets. In the afternoon you will generate your first map using public health data.


Who is this course suitable for? This course is for researchers who want to start looking at spatial or social variations in their data and generating maps to present results. The course will assume that your knowledge of spatial scales and generation of maps is zero. Examples will all be from a public health context.

Cost:

70 (students)

120 (academic, public and charitable sector employees)

300 (private sector)





Introduction to QGIS<https://www.cdrc.ac.uk/events/introduction-to-qgis-4/>

15th March 2019 @ 9:30 am - 4:30 pm

Leeds Institute for Data Analytics, University of Leeds

Course Tutor: Rachel Oldroyd

This 1 day interactive course provides a practical introduction to QGIS; a free, open-source Geographic Information System. You will learn the principles underpinning vector-based geographic data analysis and learn to undertake tasks such as sourcing, loading and interrogating data; creating professional map outputs, preparing geographic data sets and undertaking spatial analysis. Short lectures will be interspersed with hands-on practical exercises with plenty of opportunity to work with your own data and seek advice regarding your own projects.



Who is this course suitable for? No prior knowledge is assumed for this course other than having basic IT skills.



Cost:

70 (students)

120 (academic, public and charitable sector employees)

300 (private sector)



Geocomputation and Data Analysis with R<https://www.cdrc.ac.uk/events/geocomputation-and-data-analysis-with-r/>

25th-26th April 2019 @ 9:30 am - 4:30 pm

Leeds Institute for Data Analytics, University of Leeds

Course Tutor: Robin Lovelace

The aim of this 2 day course is to get you up-to-speed with high performance geographic processing, analysis, visualisation and modelling capabilities from the command-line. The course will be delivered in R, a statistical programming language popular in academia, industry and, increasingly, the public sector. It will teach a range of techniques using recent developments in the package sf<https://github.com/r-spatial/sf> and the 'metapackage' tidyverse<https://www.tidyverse.org/>, based on the open source book Geocomputation with R<https://geocompr.robinlovelace.net/> (Lovelace, Nowosad, and Meunchow 2019).



Objectives:
         Be able to use R and RStudio as a powerful Geographic Information System (GIS)
         Know how R's spatial capabilities fit within the landscape of open source GIS software
         Be confident with using R's command-line interface (CLI) and scripting capabilities for geographic data processing
         Understand how to import a range of data sources into R
         Be able to perform a range of attribute operations such as subsetting and joining
         Understand how to implement a range of spatial data operations including spatial subsetting and spatial aggregation
         Have the confidence to output the results of geographic research in the form of static and interactive maps.

Who is this course suitable for? Delegates must be an R user already, having at least completed a basic introductory course such as DataCamp's free introduction to R<https://www.datacamp.com/courses/free-introduction-to-r> course or equivalent.


Early Bird rates (valid until 18th March 2019)
400 - Students
600 - Academics, charitable and public sector
800 - Other


Introduction to R<https://www.cdrc.ac.uk/events/introduction-to-r-3/>

29th April 2019 @ 9:30 am - 12:30 pm

Leeds Institute for Data Analytics, University of Leeds
Course Tutors: Drs Richard Hodgett and Emmanouil Konstantinidis

This half-day course will provide you with an introduction to the analytical programming language R. The course will focus on data pre-processing and visualisation, two of the key steps in understanding and generating insights from data. During the course you will learn about the benefits or R, how R handles different data types and how you can begin to use R to solve complex data science, machine learning and statistical problems. Specifically, you will work with R and its various packages to import, clean, manipulate and visualise real world data. The course assumes no knowledge of R or statistics.


Objectives:

  1.  To familiarise attendees with R, including the RStudio integrated development environment.
  2.  To learn more about the broader R ecosystem - i.e. packages that extend the functionality of 'base R'.
  3.  To introduce R's syntax and a variety of primary functions.
  4.  To learn how to tidy and manipulate data using R.
  5.  To learn how to utilise data visualisations to communicate your results.
Who is this course suitable for? No prior knowledge is assumed for this course other than having basic IT skills.


Cost:

40 (students)

60 (academic, public and charitable sector employees)

150 (private sector)



Please click on the title for more information on content or to make a booking.

Please email Kylie Norman<mailto:[log in to unmask]> for further information or if you are booking using a Leeds internal account.



Best Wishes,



Kylie Norman

Administrative Assistant

Consumer Data Research Centre (CDRC)



Leeds Institute for Data Analytics (LIDA)

Level 11, Worsley Building

University of Leeds

LS2 9JT



Email: [log in to unmask]<mailto:[log in to unmask]>

Tel: 0113 3430242

Please visit our website: http://cdrc.ac.uk<http://cdrc.ac.uk/>

You may leave the list at any time by sending the command

SIGNOFF allstat

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