Geographical data are increasingly available for agriculture and environment applications, as shown by the ever growing use of satellite imagery, expanding use of drones for image capture in agriculture and environment management and ubiquity of GPS technology in modern data acquisition tools. Therefore, professionals in agriculture and environment, among others, need to overcome their current limitations in extracting and exploring those important and frequently freely available resources. Professionals might also have access to large sets of spatial information through their own institutions (either public or private) without having the necessary knowledge and skills to be able to process it. To be able to address those challenges, the user does not absolutely need to be an expert in GIS or Statistics, but needs to have a sufficient background to address the problems in hand. This projects aim at improving the skills of those professionals in that respect. It will help them to use available open source tools to extract and analyze spatial data which are relevant for their professional activity. This project is developed by three partners : the University of Lisboa, which have a strong background on teaching courses on GIS and spatial data analysis with R software, SupAgro Montpellier, which has skills on Bayesian statistics, an experience in the creation of mooc and offer technical and logistic supports to the project (including a video studio), and the University of Liege, which has experience in the organization and management of a master degree in applied statistics and has a dedicated higher education pedagogical department (IFRES) which can provide the needed support during the construction and evaluation of the learning modules. Year one will be dedicated to the creation of the training material. In addition to the online communication tools, the transnational meetings will be the occasion to exchange practices , meet local stakeholders and integrate their constraints into the project. During year 2, the created cursus will be tested on a panel of selected students originating from the 3 partners. The efficiency of the chosen learning techniques (MOOC, blended learning) will be monitored and analyzed to fine tune the learning activities of year 3. Learning activities of year 3, corresponding to 6 ECTS of intensive courses on spatial data analysis with open tools will be held in Belgium, but transferable in partners' institutions after the project. The activities will take form of an introductive MOOC followed by blended learning activities, with a maximum of two weeks of face to face activities. During year 3, the results of the monitoring of the learning activities of the project will be proposed for a communication in a pedagogical conference, possibly one of the International Academy of Technology, Education and Development (IATED), INTED or EDULEARN. Promotion of the project will be conducted through the creation of a website, a video teaser, a flyer and through the organisation of a local seminar in each partner's institution, and one international seminar on year 2 in Belgium. For the target groups and stakeholders (entreprises active in life sciences needing expertise in spatial data analysis), the project will fill a gap in the training offer, permitting to acquire key competences in spatial data analysis in a organisational design especially tailored for their needs and constraints and therefore increasing competences in applied statistics for spatial data analysis on the job market and the partial filling of the high demand for spatial data analyst workers . Apart from the creation of the learning modules themselves, we expect creating emulation between partners of the project with other organisations active in data analysis and innovative pedagogy, and using the created contacts as well as the experience gathered during the project in order to improve the learning offer. The expected impact is a greater experience in transnational teaching, to explore the benefits and constraints of such programs. We also expect to create a worthy emulation on innovative teaching methods by exchange of our mutual experience, acquired before and during the project and use the project as a same scale laboratory of learning practices, which will be used to test the long term feasibility of a greater scale transnational program, e.a. European Master Degree.