04-651-A   Applications of Machine Learning in Africa

Location: Africa

Units: 6

Semester Offered: Fall

Course description

Recent advances in machine learning and an increase in the availability and collection of massive data sources, such as satellite images, social media data, and call detail records from mobile phone operators, have begun to transform our understanding of critical challenges facing the developing world, especially within the African continent. In particular, these data sources can offer a more timely, complete, and cost-efficient alternative that has the potential to guide more effective decision-making. However, in order to maximize the value of alternative data, users need to have an awareness of their sources and value, knowledge of how and when to use alternative data to obtain meaningful insights, and a deep appreciation of a range of ethical issues, such as privacy. In this course, students will become conversant with current research that uses alternative data to better understand the social and economic realities of people and communities in African countries. Through readings of recent work, students will also analyze the opportunities and challenges presented by the use of alternative data. Upon successful completion of this course, students will be more familiar with the use of current alternative data approaches in research. In addition, students will be able to formulate research questions that are grounded in a review of relevant literature and answerable through an analysis of alternative data and identify existing data sources and relevant machine learning approaches that can be used to answer these questions. This course is designed as a seminar. Therefore, it is based on interactions between the students and the instructor, grounded on readings of current research as well as students’ own writing.

Learning objectives

  • Critically analyze current research that uses machine learning approaches with alternative datasets
  • Discuss the opportunities presented by these approaches in understanding and improving outcomes in various sectors of African countries, such as healthcare, education, and financial inclusion
  • Analyze the limitations and challenges presented by these datasets, such as privacy concerns
  • Develop an original research proposal grounded in the current literature which addresses issues of socioeconomic development in Africa


Alain Shema