ARCHIVED | Event | Essex Big Data and Analytics Summer School 2017

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ARCHIVED | Event | Essex Big Data and Analytics Summer School 2017

Archived – Please note this event took place in the past and has been left here for reference purposes. View our full list of events to see what we have coming up or if there is a particular type of event you are interested in.

Big Data and Analytics Summer School 2017 run by the Institute for Analytics and Data Science

Date: 24 July – 4 August 2017
Venue: University of Essex, Wivenhoe Park, Colchester, Essex

We are delighted that some of our researchers are participating in this year’s Institute for Analytics and Data Science big data summer school at the University of Essex.

The Essex Big Data and Analytics Summer School at University of Essex is open to both internal and external delegates. The summer school is for graduates, postgraduates, researchers and professionals in the emerging fields of data science, analytics and big data who would like to find out more or be updated on the current trends and developments in this exciting and fast-developing field.

Whether you are interested in the curation and management of big data, advanced techniques and methods including artificial intelligence and statistical methods, or applications of big data in fields ranging from business and finance to bioinformatics, you will find a set of relevant courses for you.

Hear about a wide range of data topics including:

Machine learning with Mahout with Richard Skeggs
An introduction to Geographical Information Systems with Professor Andrew Lovett

Courses are available covering a wide range of topics from multiple perspectives. They are being delivered by experts in that field, internal and external, academic and professional. Over thirty courses will be delivered in parallel sessions over the ten days.

Participants can attend either one week or both and can choose the courses of most interest to create your own programme of study.

For more information and to book, visit the IADS event page.