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LIDA Seminar Series 19th December 2019

Category
LIDA Seminar
Date
Date
Thursday 19 December 2019, 12:30pm - 3pm
Location
Training Suite 11.06, Level 11, Worsley Building, University of Leeds, Clarendon Way, Leeds, LS2 9NL
Organiser
LIDA, 0113 343 9680, lida@leeds.ac.uk
Category
Tags

This seminar will consist of a 60 minute introduction, followed by a 90 minute practical workshop and will be held in Room 11.06, Worsley Building, at 12.30 on Thursday 19th December.

Seminars are free and open for all to attend. No prior booking is required.

#LIDAseminar

 

PLEASE NOTE - To take full advantage of the workshop, participants are asked to bring their own laptops, and must have a Google account with an activated Google Cloud Services account under the free trial schema. Also, it is highly recommended that MS Windows users install MobaXterm as this makes working with remote machines much easier. Previous programming experience and knowledge of the Bash shell or any other Terminal shell is recommended.

 

Workshop: Cloud-based Virtual Machines for research

By: Daniel Valdenegro (University of Leeds)

Abstract: In this workshop we will introduce the use of Virtual Machines (VM) for data storage, and data manipulation and analysis. We will define a pipeline that will allow us to create and set a task in a reliable and secure way without the need for constant supervision from the user, making use of the tools provided by the cloud service.

The topics covered in the workshop will be:

  • Creating our first Virtual Machine in Google Cloud Services.
  • Installing tools in your VM (e.g. R, Python, Golang, SQLDBs, NonSQLDBs, etc.)
  • Creating different forms of daemons to run in the background for silent and reliable data manipulation processes.
  • Creating scheduled jobs.
  • Creating a High-Performance Cluster.

About the instructor
Daniel Valdenegro is a PhD student in Computational Social Science at the University of Leeds and former Data Analyst and Junior Researcher at the Social Psychology Lab of the Pontifical Catholic University of Chile. He is passionate about data analysis and quantitative social research methodology, with experience working with R, Python and JavaScript. His research interests are in the use of 'big data' from digital sources -such as social media, IoT or just general digital footprint- to model human behaviour. His current PhD project attempts to use the public digital footprint on social media of populations that are undergoing periods of social unrest, to extract their general emotional pattern, all this to build a predictive model of activism based on theses parameters.