To ensure the effective deployment of artificial intelligence, it is essential to equip scientists and professionals with a strong foundation in AI sciences, mastery of advanced tools and concepts, and the ability to apply them in innovative ways.
Lifelong learning to update the skills of the current workforce is also a key action to ensure responsiveness and the full uptake of short-term opportunities.
To support this deployment, the ENACT educational programme is built around the three pillars of learning:
- Learning to Learn
- Learning to Do
- Learning to Be
Université de Lorraine and the University of Strasbourg will soon introduce a new education and training offer.
Learning to Learn
Excellence in AI education is a top priority, with specialised courses in computer science, mathematics and statistics. Université de Lorraine and the University of Strasbourg offer high-level AI education and training at all levels, including bachelor’s, master’s and engineering programmes.
A strong emphasis is placed on integrating AI across disciplines through AI+X courses. These courses introduce AI at earlier stages of study and provide specialised AI training at more advanced levels, leading to the creation of new degree programmes such as Data Analytics for Economics and Business Management. Master’s and engineering students can also choose AI-focused course units to complement their disciplinary expertise, leading to specialised qualifications in areas such as Law and AI, Life Sciences and AI, and more.
Finally, AI awareness is promoted through introductory MOOCs designed for students with limited prior exposure to the field, paving the way for more advanced learning opportunities. Lifelong learning programmes developed in collaboration with industrial partners are also offered. These include short courses focused on advanced skills as well as longer programmes leading to certification, benefiting both professionals and academics seeking to strengthen their expertise in AI.
Learning to Do
ENACT promotes an interdisciplinary approach and group projects across different levels of higher education. The objective is to encourage the practical application of knowledge and collaboration between disciplines to address complex challenges. We want students to gain a concrete understanding of how different fields interact in real-world situations. We will also offer industry placements and data-driven challenges, such as hackathons, enabling students to put their AI skills into practice. Overall, ENACT aims to provide a dynamic learning environment that prepares students to tackle real-world challenges while giving them access to the resources and opportunities they need to learn, develop and succeed.
Learning to Be
Students will receive mandatory training in AI ethics and regulation, supported by practical scenarios to encourage real-world application. This training is designed to promote responsibility and integrity in the design and governance of AI systems. It is also open to doctoral candidates and faculty members wishing to integrate AI into their programmes. This commitment ensures that AI is developed and taught on a strong ethical foundation.
