Professional Evaluation of Data Science Curricula in Nigerian Universities

The adequacy of data science education in Nigerian universities determines whether the country's tertiary institutions can produce graduates ready for industry demands, and professional evaluation of existing curricula provides evidence for targeted reform. This study evaluated data science and related programmes at six Nigerian universities spanning all geopolitical zones: University of Lagos (SW), University of Nigeria Nsukka (SE), University of Benin (SS), University of Abuja (NC), Bayero University Kano (NW), and University of Maiduguri (NE). A professional curriculum evaluation methodology was employed, combining document analysis of programme syllabi against a competency framework derived from industry demand surveys, structured interviews with 18 programme coordinators and 12 data science industry hiring managers, and alumni surveys at three institutions. Evaluation showed that Python programming was covered in all six programmes, but machine learning was adequately addressed in only four. SQL database skills were included in five programmes but lacked depth. Statistics curriculum was strong across all six. Deep learning, cloud computing, and data engineering were absent or minimal in five of six programmes. Real-world project experience was inadequate in all six, with capstone projects being optional in four. The study recommends a National Minimum Data Science Curriculum Standard developed through collaboration between NUC, NITDA, and industry representatives, mandatory industry partnership for capstone projects, and supplementary cloud computing laboratory access funded through TETFund innovation grants.

Keywords: data science curriculum evaluation, Nigerian universities, NUC standards, industry readiness, programme quality