The context of the VALENCE project stems from the current circumstances regarding the labor market demands for qualified personnel in the field of artificial intelligence (AI), specifically of
machine learning (ML) and data science (DS). While the traditional information technology (IT) sector has been dominating labor market requirements in the last few decades, the recent rise and everyday presence of modern-day scientific and industrial phenomenons such as the Internet of Things (IoT) and Industry 4.0 pose unique needs for workforce well versed in more than the until now usual IT knowledge and skill base. Indeed, the increasing prevalence of AI will completely change the job market of the future. The present-day data driven reality of complex, dynamic, and interdisciplinary scientific, economic, and industrial landscapes requires well prepared and qualified people present at every hierarchy level within modern companies and organizations. Because of this, companies increasingly seek to hire employees with a grasp of the fundamental principles of working with (big) data and applying machine learning methods to design
and train intelligent systems for deployment. In fact, almost all companies can benefit from a firm grasp of machine learning and data science principles by their employees. On the
other hand, there is a persistent and worsening lack of skilled labor in the tech industry at a European level, an issue that has been reflected in the Innovation Union research and
innovation policy.
Therefore, it is up to education on a global level to keep up the pace with the developing state of affairs. While there is no shortage of top-level universities, research centers, or other
educational organizations throughout the world which extensively cover machine learning, data science, and artificial intelligence at the highest levels of education, vocational
education and training is left behind. This is a worry because the world of IoT and Industry 4.0 is not only for the engineers and scientists, but also for the technicians and workers, who
must be ready to work with big and complex data.
Accordingly, just as in the past decades vocational education programmes had taken upon themselves to step up and introduce IT to their students in an effort to keep up with the
developing needs for skilled personnel of the labor market, it is now time to undertake similar actions in order to keep the youngest people in touch with the recent trends in industry
and science, and update curricula to include courses on data management and basic machine learning. Thus, young professionals emerging fresh from their vocational training would
be well suited for work and for quick adaptation in many demanding areas. Our project will develop a platform which will completely integrate with the vocational study courses for the
purpose of efficient teaching of young vocational students the basics of data processing, data visualization, and machine learning. More importantly, it will be our objective to achieve
this by taking into account the realistic needs of the modern-day labor markets, and to tailor our product according to the feedback and demands from the students and teachers
themselves.
Our project is primarily focused on achieving this locally and regionally, with a long-term target of developing an efficient and scalable platform that can be applied anywhere. The reason for this is quite simple and obvious: in the world of globalization every country competes on the international market and develops its industry and economy outwards, towards collaboration and trade instead
of isolation.