Big data techniques and applications in the agri-food system
The volume of available data has doubled in the past five years. This is creating new opportunities for business and science alike, and can assist the agri-food system to create more powerful processes
CIHEAM and ICARDA
Key reasons to attend this course
Learn about the methods and computational architectures used to give answers to previously unanswerable questions using Big Data analytics.
Better understand a range of analytical techniques that can be applied to big data including traditional statistical methods, machine learning and artificial intelligence.
Be aware of the issues that arise when transferring big data analytics to a production environment.
Gain experience in organising data using traditional methods, such as SQL, as well as more modern approaches including NoSQL and the Semantic Web.
Participate in real world examples of business applications of big data.
Gabriel Anzaldi, Eurecat, Lleida (Spain)
Daniel Arrobas, John Deere, Madrid (Spain)
Javier Betrán, Bayer, Toulouse (France)
Chandrashekhar Biradar, ICARDA, Cairo (Egypt)
Shirley Coleman, Newcastle University (United Kingdom)
Xavier Domingo, Eurecat, Lleida (Spain)
Lluis Echeverría, Eurecat, Lleida (Spain)
Monika Solanki, Agrimetrics, Reading (United Kingdom)
Fred Van Eeuwijk, Wageningen UR (The Netherlands)
Expert from Carrefour
(lectures and practical work)
10 leading international experts
Course given in English
For all info see here http://edu.iamz.ciheam.org/BigData/en/index.php