The work in this article focuses on the modelling of an intelligent digital ecosystem for educational and career guidance for students and young people seeking their first job or retraining. To do so, the multi-expert system paradigm was used to aggregate the different expertises required for a good guidance, the multi-agent system principle was used to have a modular and easily scalable ecosystem. Indeed, the agents of the system communicate with each other using the FIPA-ACL language, in a collaborative vision, throughout the orientation assistance process to perform tasks such as proposing business sectors, occupations, training, and training paths. The ontologies of the Semantic Web have been used to have a complete semantic description of the shared information and to promote communication between the different software agents of the ecosystem. Big Data principles have also been deployed to manage and exploit structured and unstructured data from different data sources related to the guidance ecosystem.
The ecosystem modeled in this way has several innovative and powerful technological and scientific aspects. Thus, in terms of design and modelling, the proposed ecosystem considers all the actors and factors involved in the guidance process, including labor market trends. In technological/scientific terms, it is based on methods that allow it to be modular and scalable.

This paper presents the use of the FAHPmethod (Fuzzy Analytic Hierarchy Process) to help young people choose the most appropriate activity sectors for their profile. This choice is based on three criteria: Professional interests, professional sub-interests and personality traits. This work is a part of a global context aiming to apply the Multi-criteria Decision-Making (MCDM) methods in the vocational guidance according to the process schematized in Figure 3.

This work focuses on the use of multi-criteria decision-making method AHP for using in educational and vocational guidance. Analytical Hierarchy Process (AHP), proposed by the mathematician Thomas Saaty in 1980, is a method of analysis greatly used in the context of a multi-criteria analysis; it allows the comparison and the choice between the preset options. To achieve this goal, a vital work, preceded the use of the AHP method, which consists in doing a prototyping of trades according to the guidance criteria and sub-criteria. The IT system based on this method allows the student to find, firstly, the activities' sectors which are the most appropriate to his/her profile, to choose subsequently the trades and finally, to identify, the potential training paths.

The computer system has become one of the centerpieces in the functioning of organizations hence the importance of an IT (Information Technology) master plan to manage its development. To find a provider for the IT master plan's realization, organizations are increasingly using tendering as the mode of awarding contracts.
This article focuses on the use of multi-criteria decision-making method AHP for analysis and evaluation of tenders during the awarding of contracts of IT master plan's realization. To achieve this goal, a painstaking work was realized, on the one hand, for making an inventory of criteria and sub-criteria involved in the evaluation of bids and on the other hand for specifying the degrees of preference for each pair of criteria and each pair of sub-criteria. Finally, a test was performed by using fictitious tenders.
The goals of this work are to make available to members of tenders committee a decision support tool for evaluating tenders of IT master plan's realization submitted by bidders and endow the organizations with effective IT master plans in order to increase the performance of their information systems.