Big Data and Analytics Summer School

Registration for our 2016 summer school is now closed. If you have any queries or would like to register you interest for our 2017 summer school please email iadssum@essex.ac.uk.

Audience

Our summer school is for graduates, students, researchers and professionals in the emerging fields of big data, data science and analytics who would like to find out more or be updated on the current trends and developments in this exciting and fast-developing field.

  • Hear keynote talks by leading experts.
  • Attend state-of-the-art courses delivered by academics from Essex and other leading institutions and our industrial partners.
  • Network with your peers in an invaluable forum for knowledge exchange.

Whether you're 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'll find a set of relevant courses for you.

Delegate interviews

In these videos, delegates explain why they wanted to come to the Essex Big Data and Analytics Summer School 2016.

Courses

Courses will be available covering a wide range of topics from multiple perspectives. Each will vary in length and are available at various levels. They will be delivered in parallel over the five days and you can choose the courses of most interest to create your own programme of study. Please see the programme and schedule below to choose your courses. Participants must attend the whole length of the course.



  • Machine learning with Mahout Richard Skeggs, ESRC Business and Local Data Research Centre, University of Essex
  • Modelling and analysis of complex systems Dr Chris Antonopoulos, University of Essex
  • Crowdsourcing and human computation Dr Jon Chamberlain, University of Essex
  • Introduction to R Professor Leo Schalkwyk, University of Essex
  • Introduction to meta-analysis Professor Elena Kulinskaya, ESRC Business and Local Data Research Centre, University of East Anglia
  • Reinforcement learning and causal inference Dr Spyros Samothrakis, University of Essex
  • Introduction to Natural Language Processing Dr Diana Maynard, University of Sheffield - FULL
  • Practical text analytics and sentiment analysis from social media Dr Diana Maynard, University of Sheffield
  • Big data methods with R Simon Walkowiak, Mind Project - FULL
  • Clustering and classification with applications in R Dr Osama Mahmoud, University of Bristol
  • Introduction to data visualisation using R Dr Aris Perperoglou, University of Essex - FULL
  • Modern combinatorial optimisation methods Dr Daniel Karapetyan, University of Essex
  • Open data science Dr David Tarrant, Open Data Institute
  • Large scale visual recognition and retrieval Dr Shoaib Ehsan, University of Essex - CANCELLED
  • Big data management systems for fun and profit Dr Nikos Ntarmos, University of Glasgow
  • Principles of big data storage and processing systems Dr Nikos Ntarmos, University of Glasgow
  • Best practice analytics Detlef Nauck, British Telecom
  • Cognitive analytics Professor Martin Spott, HTT Berlin - FULL
  • Techniques for securing IoT devices in a cloud environment Dr Gareth Howells, University of Kent
  • Hadoop fundamentals for the cloud Dr Martin Fleury, University of Essex
  • Replicating and publishing data, and the role of big data versus national statistics Louise Corti and Sharon Bolton, UK Data Service, University of Essex
  • Exploring household energy data using the Hadoop ecosystem Peter Smyth, Dr Sarah King-Hele, Aidan Contron, UK Data Service, University of Manchester and University of Essex
  • How to understand Big Data: Strategies for understanding your big data and getting new knowledge from it Nathan Cunningham, Libby Bishop, Felix Ritchie, UK Data Service, University of Essex - FULL
  • Stream processing and data analytics for Smart City Nazli Farajidavar and Dr Sefki Kolozali, University of Surrey
  • Building agent based models for theory and empirical research Dr Abhijit Sengupta, University of Essex
  • Bayesian computational methods with applications in R Dr Hongsheng Dai, University of Essex
  • Actuarial/financial modelling with applications in R Dr Spyros Vrontos, University of Essex
  • Data Science meets Optimisation Dr Andrew Parkes, University of Nottingham
  • Agent-based modelling of social systems for policy making Dr Peter Barbrook-Johnson, University of Westminster
  • Visual object recognition and tracking Professor Ales Leonardis, University of Birmingham – NEW COURSE
  • A hands-on introduction to Spark Richard Skeggs ESRC Business and Local Data Research Centre, University of Essex – NEW COURSE

  • Data protection and liability in the age of big data Dr Audrey Guinchard, Dr Anthony Vickers University of Essex
  • Human rights in the era of big data and analytics Daragh Murray, University of Essex
  • Replicating and publishing data, and the role of big data versus national statistics Louise Corti and Veerle Van Den Eynden, UK Data Service, University of Essex

  • Trading, cost and regulations in the big data era Dr Yi Cao, University of Essex
  • Actuarial/financial modelling with applications in R Dr Spyros Vrontos, University of Essex
  • Big data and finance Professor Neil Kellard, University of Essex
  • Science and big data Andrew Harrison, University of Essex - CANCELLED
  • Stream processing and data analytics for Smart City Nazli Farajidavar and Sefki Kolozali, University of Surrey
  • Open data for smart cities Ben Cave, Open Data Institute
  • Large scale visual recognition and retrieval Dr Shoaib Ehsan, University of Essex - CANCELLED
  • From big data to big value Richard Mason, Intel - CANCELLED
  • Exploring household energy data using the Hadoop ecosystem Peter Smyth, Dr Sarah King-Hele, Aidan Contron, UK Data Service, University of Manchester and University of Essex

Keynote speakers

  • A Data Manifesto, Hetan Shah, Executive Director, The Royal Statistical Society.
  • List[Corporation].map(x => google(x)).reduce(_ + _) === ???, Harry Powell, Head of Advanced Data Analytics, Barclays PLC
  • Deep reinforcement learning, Hado van Hasselt, Research Scientist, Google Deepmind
  • What’s next in (data) journalism?, Megan Lucero, Data Journalism Editor, News UK

Social and networking events

There will be plenty of opportunities throughout to network with your peers and presenters. Each week there will be a social event on campus with food and drink for the evening included in the registration fee.

  • Monday 5 September - drinks reception and buffet held at the Silberrad Student Centre.
  • Tuesday 13 September - formal dinner held of Wivenhoe House Hotel.

Venue

The Essex Big Data Summer School will be held at our Colchester Campus.

Accommodation

If you'd like to stay at the Colchester Campus during the conference, we have designated self-catering, en-suite accommodation available for £37.50 per night (when staying between 4 nights and 2 weeks) from 3 - 18 September.

Book a room and use the promo code 'Bigdata16' to ensure you receive the discounted rate.

Fees and registration

The registration fee includes all tuition, refreshments during the teaching day (mid-morning refreshments, lunch and mid-afternoon-refreshments) plus one social event per week which includes food and drink for the evening.

Contact us

For any enquiries contact Emma McClelland, Summer School administrator by email iadssum@essex.ac.uk or phone 01206 873496.

Previous Summer Schools

  • Our 2015 Summer School

    Video of our 2015 Summer School

    Feedback from our 2015 Summer School

    "The organisation, networking and content of the Summer School were excellent."
    "I came because I googled data mining and analytics events, this seemed too perfect. I'm glad I came, all relevant information and documentation was sent in advance, great organisation, it brought together researchers, academics and industry professionals to give good overview of data technologies."
    "Thank you for organising such an interesting Summer School."