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.
Understand a relevant state of the art Big Data architecture and tools with a simple example
Accessing data from external sources
Data integration
Data exploration
Consumer segmentation for targeted marketing
Predict plant growth from DNA and environmental conditions
Open data and other public data sources
The course is targeted to different actors in the agrifood system, such as: data managers, professionals involved in precision agriculture and livestock farming, food processors and distributors, marketing and sales managers, members from the administration involved with data advising decision makers and final users, specialists from consultancy services, and R+D experts involved in data analytics. Participants are expected to have a quantitative background, and some familiarity with scripting languages (e.g. R, Python).
The course will be held at IAMZ-CIHEAM in Zaragoza from 17 to 21 June 2019.
Application deadlines:
8 April 2019 - if you need a visa or intend to apply for a grant to attend the course. The deadline will be extended for candidates not applying for a grant and not requiring a visa while places are available.
Registration fees for the course amount to 500 euro. This sum covers tuition fees only.
Candidates from CIHEAM member countries (Albania, Algeria, Egypt, France, Greece, Italy, Lebanon, Malta, Morocco, Portugal, Spain, Tunisia and Turkey) and from ICARDA Middle East and North Africa (MENA) partners may apply for a limited number of full or partial scholarships offered by the organizing institutions covering registration fees, travel and accommodation.
Candidates from other countries who require financial support should apply directly to other national or international institutions.
It is compulsory for participants to have medical insurance valid for Spain. Proof of insurance cover must be given at the beginning of the course. Those who so wish may participate in a collective insurance policy taken out by the Organisation, upon payment of the stipulated sum.
Gabriel Anzaldi graduated with honours as an Electronic Engineer; performed electronics advanced studies and has participated in technology transfer activities in the USA and the French Republic. Mr. Anzaldi holds an interdisciplinary experience, more than 20 years across multiple positions collaborating with SMEs and large companies. Currently, co-operates with the EC as Expert in Digital Strategies, including Artificial Intelligence, Big Data and IoT applied to systemic management in agriculture, water and industry at large. His research team is focused on the implementation of solutions to discover domain insights and systems interoperability along inter-domain value chains.
Head of Geoinformatics Units and Principal Scientist (Agroecosystems) at the International Center for Agricultural Reseach in Dry Areas (ICARDA), a CGIAR Research Center. Dr. Chandrashekhar Biradar is a head of Geoinformatics Units and principal agroecosystems scientist who heads GeoAgro, Big Data and ICT innovations in agroecosystem research and outreach. Dr. Biradar graduation in forestry and agricultural sciences, Master's in Genetic Engineering and Ph.D. in Satellite Remote Sensing and Environmental Sciences. The post-doctoral fellowships with the International Water Management Institute and Institute for the Study of Earth, Ocean and Space (EOS) at the University of New Hampshire, USA. Before joining ICARDA, he served as a research professor, research scientist, senior research scientist, and manager at the University of Oklahoma, Norman, USA while working on number of federally funded projects. Over the last 21 years, he has played a key role, as one of the lead researchers, in producing first satellite sensor-based approaches for mapping agroecosystems at global to local scales. Developed and demonstrated number of EOS based big-data analytics, algorithms and platforms for quantification of the land use/land cover, cropping systems, biodiversity, gap analysis, land and water productivity, pest and disease risks, climate change and project impact assessments. His spatial research is been focused on the science-based innovations for inclusive agroecosystems. Dr. Biradar has authored over 200 publications, which include over 85 peer reviewed ISI journal publications, 24 books/chapters, and over 100 other publications. Dr. Biradar has been recognized with a number of international awards and honors such as the Young Scientist of the Year, Outstanding Young Scientist, Best Team Initiative, Outstanding Team Member, Board Member, Steering Committee Member, and Panel Member of Geoinformatics for Agriculture, Working Group on high resolution remote sensing, advisory member of WMO/GWP's Integrated Drought management Program (IDMP), and AASIO's Outstanding Young Scientist Award. His current research focus is on Big Data and digital augmentation for accelerating ecological intensification for resilient agroecosystems in the dry areas.
Dr Shirley Coleman is Technical Director of the Industrial Statistics Research Unit, School of Mathematics, Statistics and Physics, Newcastle University and a visiting scholar at the Faculty of Economics, Ljubljana University, Slovenia. She works on data analytics in Small and Medium Enterprises (SMEs) and contributed a highly ranked impact case study to Newcastle University's Research Excellence Framework. She is the academic lead on Innovate UK funded Knowledge Transfer Partnerships developing data science capabilities, and specialises in statistical and machine learning techniques applied to company data. She publishes in trade and academic journals and is co-editor of several books. She is a past President of the European Network for Business and Industrial Statistics (ENBIS), an elected member of the International Statistics Institute and a Chartered Statistician of the Royal Statistical Society, instrumental in mentoring early career statisticians and developing relationships with business and industry.
Xavier Domingo is responsible for the Applied Artificial Intelligence line of the Smart Management Systems Unit of Eurecat. He has a Diploma in Advanced Studies in Artificial Intelligence (UdL) and a degree in Computer Engineering (UPC). He has extensive experience in applied Data Science using hybrid IoT and Big Data architectures, including intelligent platforms with capacities related to predictive maintenance, planning and resource optimization, machinery monitoring and control, and traceability applied to the agri-food sector and manufacturing industry, as well as applications in other sectors such as logistics, environmental, transport and water distribution, and functional food. He collaborates as a senior consultant in logistics and services companies, with more than 15 years of experience. He is part-time Associate Professor in the Department of Computer Science and Industrial Engineering in UdL, where he is involved in teaching related to advanced software architectures. He has participated in several European Commission funded research projects (FP7, H2020) such as FIWARE4WATER, SIM4NEXUS, WIDEST, WatERP, and several funded by the Spanish government (Retos, PID, CENIT), such as iCODER, Interacciona, SOM, or HENUFOOD, among others.
Lluis Echeverría is senior researcher of the Smart Management Systems (SMS) unit of Eurecat. He has a Master in Artificial Intelligence and Big Data (UdL), a graduate in Computer Engineering (UdL), specialized in Information Technology, and a Topographic Technical Enginery (UPC). He has been part of the Person-Computer Research and Data Integration Group (Griho) of the University of Lleida, in the InVID project (H2020), giving support to research on copyright management of audiovisual content on social networks. He has experience on Data Science solutions implementing and deploying BigData/IoT hybrid architectures, based on referent technologies to process massive amounts of data in real time, and also studying and analysing that data through different Data Mining and Artificial Intelligence techniques. He is currently involved in R+I+D projects, at European, National and regional level, related to Data Mining, Artificial Intelligence, IoT and BigData topics applied to the domains of Agrifood, Industry 4.0, water management (in all its cycles), predictive maintenance or efficient and intelligent resources management, having special interest on the study and creation of intelligent agents using Reinforcement Learning techniques (area of machine learning).
Dr. Monika Solanki is Principal Data Scientist at Agrometrics and has a PhD in Computer Science, a postgraduate diploma in Advanced Computing with Data Communication and Networking and a degree in Engineering. Her research focuses on developing ontology design patterns, models and applications in the area of knowledge representation and reasoning using Semantic Web technologies and Linked data principles. She has worked extensively on building ontology-driven frameworks for bridging the gap between data and software engineering, developing and implementing stream processing algorithms and models for tracking and tracing in supply chains, using event based pedigrees over GS1 standards and developing decision support systems for the clinical and bioenergy sectors. Dr Solanki has extensive experience in designing and developing ontological domain models, curating linked datasets, implementing Semantic Web applications and Web services for a number of interdisciplinary projects spanning the boundaries of Big data, Software Engineering, Computer Science, Bioenergy, Clinical trials, Archaeology and Plant Biology. Besides research, she is passionate about travelling, hiking, conserving nature and wildlife and vegan cuisine.
Head of Big Data Architecture in Carrefour Spain
I'm a professional with more than 18 years of experience in IT within the RETAIL sector (Carrefour Spain). Through my career in the company, I've led IT projects in promotional intelligence and pricing.
Graduate in Big Data technologies at the UNIR (International University of La Rioja) and at the UTAD (University Centre of Technology and Digital Art) currently, I am head of Big Data architecture solutions and techniques.
From this department of Big Data Architecture, we develop transversal components with Big Data technologies for the other business units.
Furthermore, we are in charge of the definition and management of Big Data architecture for all Carrefour Spain's projects.
IAMZ-CIHEAM
