About the Course

As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to transform development research and policy. Recent examples show how satellite imagery and deep learning can be used to identify and target pockets of extreme poverty; how mobile phone metadata can help track and stop the spread of malaria and Ebola; how social media analytics can improve disaster response; and how machine learning algorithms can help smallholder farmers optimize planting and harvesting decisions – to name just a few examples. Through a careful reading of recent research papers and through hands-on analysis of non-traditional datasets, this course introduces students to the opportunities and challenges for dataintensive approaches to international development. Students must have graduate training in econometrics, machine learning, or a related field.