We study the impact of a program designed to enhance data literacy on graduate students’ skills and academic outcomes in a large Italian university. The program (i.e. a minor) targets students who are expected to have weak quantitative competences and offers 120-hours training focused on improving the ability to interpret and process data, in addition to the regular courses of the master program in which students are enrolled (i.e. their major). The admission process to the minor is characterized by rationing, resolved by random assignment of available slots to applicants. Exploiting the resulting exogenous variation for identification, we find that the program largely improved digital literacy of participants with low pre-treatment levels of numeracy. Despite the additional effort required by the program, we can rule out any slowdown in the progress of the academic career in the major master program of participating students.