Training modules

Training modules

Modules and courses for PhD students and engineering students, short professional training sessions & MOOCs, developed by our partners, supported and labelled by #DigitAg.

Higher education

Junior Research Lab (JRL)
8-week course delivered in its entirety in English (level B2)
If followed in its entirety, the course allows you to benefit from 14 ECTS credits
website

Agricultural engineer Data science option for agronomy and agri-food
Public: Engineer - 3rd year - semesters 9 & 10 - master of science 2 (Montpellier SupAgro)
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Agronomic Engineer Option AgroTIC for Agriculture and the Environment
12 weeks of common core courses, followed by a choice of a personalised course over 4 weeks
website

Continuing education

Certificate of Advanced Studies in Geomatic

Post-master's level training for managers, senior technicians and engineers wishing to learn about the design and implementation of IS/GIS (information system/geographic information system) projects.
18 days minimum, personalised according to the training needs of the candidate
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Data Sciences

University Diploma Scientific Data Management (SDM)
Delivered in its entirety or in modules
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Data Sciences for Agriculture

Objectives; Acquire the basics to manipulate the main data science methods for prediction purposes

Learn the real practice of these methods through examples and practical work with R and Python software
Public: Engineers and researchers working in the fields of agriculture and the environment
Doctoral students in agronomy and ecology who have a data science component in their research project and who have a basic knowledge of R software
Reduced rate: 550€ HT for PhD students funded or labelled by the #DigitAg convergence institute
Contact: François Brun at Acta - francois.brun [AT] acta.asso.fr

website and inscriptions

Text mining for agricultural and health risks

Public: Engineers, researchers, PhD students working in the fields of agriculture, agri-food and environment
Acta- 25 & 26 May 2021 distance learning - 2 mornings (6H)
Pre-requisites: basic knowledge of R software
website and inscriptions

MOOC

No MOOC for the coming period