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There is currently a high demand for professionals with digital skills in the areas of Information and Communication Technologies. As such, in future this trend is expected to increase. Higher education institutions are unable to train adequate numbers of qualified people to respond to employers' requests. In other areas, it is expected that increasing computerization and automation will have a significant impact on reducing certain types of jobs, which highlights the need and importance for many workers to develop new digital skills in order to be better prepared to face future challenges. It also seems clear that many of the needs may be met by people who, while not having a higher education in ICT fields, such as that taught in higher education institutions, these can be suppressed by people with specific training which is more focused on a particular technology or focused on certain development niches. In this context, low-code development platforms can play an important role in training or retraining people from areas with lower market demand for ICT areas. Their characteristics and potential make them suitable for technicians with higher qualifications in other areas, and other professionals, to acquire new skills through retraining or supplementing / recycling pre-acquired basic knowledge that may become productive labour in the IT world. In this paper we describe a strategy, and several case studies, where a low-code development platform is used to reskill STEM professionals and/or professionals who, having basic IT knowledge are in precarious activities, to perform ICT professional activity. This strategy not only contributes to the needs of IT professionals but also enables many professionals to make timely retraining into areas of greater competitiveness, greater job stability and better working conditions. Throughout the paper, we present case studies that are part of this strategy and that have had positive results. These case studies include Enterprise-Higher Education collaborative training, reskilling for unemployed people with higher education in other areas, and training for those who are active, working in areas where labour needs are likely to decrease in the mid-term. The paper also identifies the benefits and contributions resulting from the use of the OutSystems low-code platform to implement this strategy.

Information and Communications Technology is a growing area with a growing demand for employees. However, there is a shortage of professionals in this area and integrated strategies are required to foster the access of more people to these areas and provide training to develop the necessary skills. In this paper we present a short course that was designed to retrain unemployed people, mainly with already a higher education level in the area of the science technology engineering and math (STEM), to be Information and communications technology (ICT) professionals. After this training, trainees will have the opportunity to significantly increase the likelihood of being able to obtain employment in ICT areas. The course described involves public entities (including a higher education institution) and a private company, which is also a demonstration of synergies between academia and business. In the paper, the context that led to the appearance of the course, the fundamentals that supported the syllabus design, the partners involved, the objectives of the several subjects, the profile of the trainees and the results already achieved are described. To explain the fundamentals of the course syllabus we explain the most original features of the course regarding the usefulness of taking advantage of the abstraction allowed by the new low-code platforms, what seem to be appropriate and facilitator for retraining professionals from STEM to ICT. This approach, using a low code platform for retraining professionals to ICT, presents in our point of view, advantages over other approaches. In short, in the paper we intend to share the work done during the design and follow-up of the course, as well as the preliminary results obtained in the meantime.