Evidence-based policy is only as good as the data that underpins the evidence. However, current approaches to data-gathering often contribute to systematic exclusion and perpetuate existing power relationships in international development. Exclusive data can render whole groups of people—for example, women or minorities—invisible for the policy process. This is particularly true for so-called ‘hard-to-reach’ populations who are supposed to benefit most from international development. Identifying how unrepresenatitve and flawed data leads to exclusive policies requires data literacy that foregrounds a justice-based approach in data collection and analysis. This course offers students theoretical and hands-on practical learning to understand what is required to make data inclusive, how to engage with those whose data is collected in ethical ways and through what mechanisms inclusive data can create policies that support diversity and inclusion. The course is taught in collaboration with researchers and data scientists from the Busara Center for Behavioral Economics in Kenya and India.