Through the Final Symposium, all African partners will be given the chance to showcase their achievements and the impact of the CBHE project on their institutions, highlighting its contribution to strengthening higher education capacities in the partner countries. The Final Symposium aims to serve as a forum for dialogue and knowledge exchange among higher education institutions, public authorities, industry representatives, and other relevant stakeholders for mainstreaming of the project outcomes while fostering future collaboration and synergies beyond the project’s lifetime. By presenting the project’s results, the developed course, training material, and innovative practices, the symposium will support evidence-based discussions on higher education reform and capacity building and promote the integration of project outcomes into institutional strategies and policy frameworks. To this end, the procedure to access all the project’s outputs will be presented to the wider audience, to allow for sustained cooperation between all actors in the field of
Data Science and AI.

Both African and European universities will present their work in Data Science and AI. African universities will showcase their increased academic capacity and their student and research projects in the field of Data Science and AI. They show how the developed courses are implemented in their regular program, including quantitative numbers on the usage of courses and students reached. They will also present their updated labs and how they are used for learning, teaching, and research. Next, they will show how cooperation with the labour market is organized through their Entrepreneurship and Innovation Bureau. Finally there is room for presenting their student and research projects, the goals, the challenges, the results and future work. The European universities make a similar presentation, allowing for inspiration and sharing of good practices. They show their program in Data Science and AI, the specific lab equipment used, and their student and research projects, the goals, the challenges, the results and future work, in the field of Date Science and AI.