MIT IDSS Spearheads Global Data Science Talent Development

In an era dominated by artificial intelligence, the fundamental importance of mathematical skills is more critical than ever. Devavrat Shah, an electrical engineering and computer science professor at MIT, argues that a strong foundation in mathematics is essential for effectively utilizing AI tools and interpreting their results accurately. As large language models and generative AI continue to transform industries, Prof. Shah emphasizes the need for individuals who can grasp the underlying concepts behind AI to fully leverage its potential.

Shah is a professor at MIT’s Institute for Data, Systems, and Society (IDSS), an interdisciplinary unit dedicated to meeting the global demand for data skills. IDSS offers online courses, including the MicroMasters Program in Statistics and Data Science, which Shah directs. This program has provided over a thousand credential holders worldwide with a rigorous understanding of statistics fundamentals.

The MicroMasters program also serves as the backbone of IDSS education partnerships. An embedded MIT team collaborates with organizations to support learners through the curriculum. Fotini Christia, the Ford International Professor of the Social Sciences at MIT and director of IDSS, highlights their partnership with the Brescia Institute of Technology (BREIT) in Peru. “Through this partnership, IDSS is training data scientists who are informing decision-making in Peruvian industry, society, and policy,” says Christia.

BREIT’s Advanced Program in Data Science and Global Skills, developed with IDSS, focuses on both technical and non-technical skills. Participants complete the MicroMasters in Statistics and Data Science, gaining expertise in statistics, probability, data analysis, and machine learning. The program also equips learners with essential career skills such as communication, critical thinking, team-building, and ethics.

Renato Castro, a BREIT learner, explains his motivation for joining the program: “I knew that artificial intelligence, machine learning, and data science was the future, and I wanted to be in that wave.” Castro has since developed data projects for groups in Peru, Panama, and Guatemala, emphasizing the program’s systematic approach to problem-solving and its impact on real-world issues.

Lucia Haro, manager of BREIT, notes that the program aims to develop problem-solvers and leaders in a growing field, contributing to economic development and positive social impact in Peru. To support this goal, IDSS provides tailored assistance to BREIT learners, with MIT graduate student teaching assistants leading regular sessions for hands-on practice and question answering.

Karene Chu, assistant director of education for the SDS MicroMasters, mentions the development of a technical assessment to support learner recruitment. This assessment gauges applicants’ familiarity with prerequisite knowledge and helps BREIT determine potential for the Advanced Program in Data Science and Global Skills.

The IDSS MicroMasters team continually evolves the program based on partner input, adding features such as a prerequisite ‘bootcamp’ to help learners from diverse backgrounds refresh their knowledge.

BREIT’s program offers opportunities to apply data skills to projects developed in collaboration with local NGOs, focusing on social impact initiatives. Diego Trujillo Chappa, a BREIT learner, improved a model for an NGO to identify potential graduate study applicants, removing biases related to their backgrounds.

Yajaira Huerta’s project focused on strategizing resource distribution for an organization building homes for the homeless during the Covid-19 pandemic. She built a clustering model to identify areas of high need, enabling the team to make better decisions.

MicroMasters Program in Statistics and Data Science credential holders have access to IDSS workshops and conferences. BREIT learners have opportunities to interact with MIT faculty and students, with some even visiting the MIT campus. According to Christia, this partnership serves as a model for developing similar networks and pipelines of data science talent globally, potentially recruiting on-campus graduate programs.