A Master of Science with a strong focus on innovation and data science for agriculture.
- Interdisciplinary teaching in English: agriculture, big data, mapping, data mining, computing, machinery, project management, sociology, etc.
- Jobs centered on new technologies
- Innovation with a project led by professionals
- Expert supervision by professionals and researchers
- The focus is on expertise in big data management, which has become a key factor in company performance and growth.
- The course is centered around the acquisition of IT and statistics techniques, data mining and machine learning applied to agriculture and the food industry in general, with a special focus on precision agriculture.
- Developing a good command of statistics software and programming languages will be a real strength for students interested in research and development in areas such as plant nutrition and plant and animal epidemiology.
All lectures are taught in English ⋅ Some lectures in collaboration with the Polish Institute of Soil Science and Plant Cultivation (IUNG) ⋅ 6-month internship in industry ⋅ Big data for companies project – Thesis
- An overview of agriculture
- Sources and reliability of data in several agricultural sectors
- Data cleaning / preprocessing / sampling strategy for big data
- Applied statistics
- Simulation methods
- Principal component analysis
- Cluster analysis
- Factorial analysis
- Discriminant analysis
- Software analysis (R, SPSS, etc.)
- Mathods of collecting data
- Unstructured data
- Multiple correspondence analysis
- Survey data analysis
- Text mining: social network analysis, etc.
- Software architectures: client-server, MVC, cloud computing, SOA, REST, microservices
- Software development: algorithmic, object-oriented programming, HMI, macro
- Data sources in agriculture: sensors, communications protocols / networks, data exchange standards in agriculture, open data, web of data
- Database design and modeling: relational, XML, multidimensional, OLAP, compared with NoSQL/New SQL databases, query languages
- Project management
- Rural sociology
- French language
- English language
- Mechanized agriculture
- Micro parcels experimental designs
- Precision agriculture
- Decision-making tools
- Cross validation method
- Neural networks
- Regression trees, bagging
- Support vector machine
- Random forests
- Kernel methods
- K-nearest neighbors method
- Sparse methods for high-dimensional data
- Distributed fils systems, Hadoop
- Parallel, distributed, massive data processing with Map Reduce
- NoSQL/NewSQL databases
- IT security for big data: vulnerabilities, protection-privacy/security policies, cryptography
- Signal image processing
- Mapping, learning QGIS software
- General linear method
- Non-linear method
- Time series modeling
- IS strategy / management, system integration
- French language (FLE)
- English language
- General engineering – Master’s degree or equivalent.
- Exceptionally, students with a Bachelor’s degree or equivalence with experience.
- Selection shall be based on the application and an interview.
Return by :
- April 28, 2017
- June 30, 2017
Tuition fees for 18 months : EUR 8,000
October 2, 2017
Data scientist / data miner
Chief data officer
Master data management
Epidemiologist (animals and plants)
Agricultural machinery designer
Research leader in agronomy
Manager of animal health observatories
Data / business analyst
Designer / developer