IEA’s first Big Data MOOC open for registration

Ed Hawkins IEA big data Mooc
Professor Ed Hawkins, Professor of Climate Science, University of Reading

Big Data and the Environment – the IEA’s new free course

Press release issued October 2017

The IEA’s new, free, online course ‘Big Data and the Environment’ is open for registration now and starts on October 30 [2017], featuring University of Reading’s Professor of Climate Science Prof Ed Hawkins.

Big Data topics covered

  • Environmental analytics and the link to big data
  • Computing power, processing and storage for environmental data
  • Open data
  • Challenges of working with data
  • Visualising data
  • Skills and knowledge of a data scientist
  • Citizen science for climate simulation and ecology
  • Real life examples of environmental analytics

It has high quality content from the team at the Institute for Environmental Analytics as well as the IEA’s world-renowned collaborators and the commitment is just 3 hours a week for 3 weeks.

Expert teachers

  • Dr Jon Blower, Chief Technical Officer, IEA
  • Prof Min Chen, Professor of Scientific Visualisation Oxford e-Research Centre
  • Prof Ed Hawkins, Professor of Climate Science, UoR
  • Dr Victoria Bennett, STFC
  • Prof David Wallom, Oxford e-Research Centre
  • Paula Marti, Deimos
  • Dr Tom August, CEH
  • Dr Fredi Otto, Environmental Change Institute
  • Barbara Percy, IEA
  • Dr Debbie Clifford, IEA
  • Richard Lamb, IEA
  • Dr Ben Lloyd-Hughes, IEA
  • Vicky Lucas, IEA
  • Tom Pinder, former IEA intern
  • Alan Yates, IEA

It also includes a look at the IEA’s exciting new urban natural capital data visualisation project BOUNTY.

Sign up here for IEA MOOC on Big Data

You can get a feel for it and sign up here

The course has been developed to support professionals as well as students and citizen scientists.

Who is it for?

Professionals will gain a better understanding of environmental data and the potential these offer to address key questions and underpin novel solutions for businesses.

Students of environmental topics and with a general interest in big data analytics will be guided through the complexities and issues surrounding the collection, curation and application of these vast data sets, including climate change, wildlife and Earth observation.

With a full glossary and accessible content aimed at a range of technical abilities the course also includes insights into how data scientists work develop meaningful visualisations.

We look forward to hearing your feedback