Abstract

Towards a Harmonized Francophone Framework for Statistical Training: Experience from Tunisia and North Africa

Training programmes in statistics, data science and artificial intelligence have expanded rapidly in Tunisian universities over the past decade. This growth, however, has taken place without a common reference framework, resulting in curricula that vary widely in content, teaching hours and targeted competencies. This paper presents a comprehensive review of statistics, data science and AI programmes offered by Tunisian higher education institutions, from bachelor’s and master’s degrees to engineering diplomas.

The first phase, already underway, involves a systematic inventory of existing degrees and programmes and the compilation of their curricula. The second phase will assess the variability and coherence of these programmes along several dimensions: the relative weight of theoretical foundations, the place of official statistics and administrative data, the integration of data science, AI and geospatial methods, the teaching of data ethics and governance, and alignment with the needs of the national statistical system. These programmes will then be compared with those of leading institutions in other North African countries.

The findings will highlight convergences, gaps in emerging skills and mismatches with the expectations of National Statistical Offices. They will inform recommendations for a minimum core curriculum suited to the Francophone context, consistent with SHaSA II and the work of STG-10, to support the mutual recognition of qualifications and the mobility of statisticians across the continent.