MIT Institute for Data, Systems, and Society builds educational partnership in Uruguay | MIT News

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In addition to making online education crucial to continued learning, the coronavirus pandemic poses the kind of global, societal challenges that must be addressed with rigorous data analysis. As the MIT Institute for Data, Systems, and Society (IDSS) and other organizations worldwide use statistics and machine learning to model infection rates, predict policy outcomes, and inform reopening plans, the need for people trained in these methods has never been more clear.

IDSS is helping to expand and promote this learning worldwide through the MITx MicroMasters Program in Statistics and Data Science. Developed by IDSS faculty, and in partnership with MITx, the MicroMasters Program focuses on four pillars of data science: probability, statistics, data analysis, and machine learning.

The IDSS mission to advance data science education through the MicroMasters Program led to a pilot collaboration with Aporta, a social impact group developing Peru’s next generation of data scientists. Building upon that success, IDSS now welcomes a new partner in Latin America: the Uruguay Technological University (UTEC) Program in Data Science.

In collaboration with Plan Ceibal, an organization in Uruguay that expands digital technologies in education and facilitates access to learning, the UTEC Program in Data Science created a blended learning program that builds upon the MITx MicroMasters Program in Data Science and Statistics. After completing four courses and a capstone exam, successful students transition to the subsequent residential master’s program at UTEC. UTEC is an MITx global pathway school, one of many worldwide offering credit toward the completion of a graduate degree to credential holders of the MicroMasters program.

“At Plan Ceibal, through the Program in Data Science, we are very excited about this new opportunity to continue strengthening our relationship with such a prestigious institution as MIT, through IDSS,” says Leandro Folgar, president of Plan Ceibal. “Together, we will keep working on our mission to advance the new generation of Latin American data scientists, positioning Uruguay as a regional hub for educational projects on innovation, entrepreneurship, and information and communication technologies.”

Through their partnership, IDSS, Plan Ceibal, and the UTEC Program in Data Science will expand knowledge and expertise in Uruguay. Plan Ceibal and UTEC will recruit and support cohorts of learners through the program; IDSS will also support these learners with live instruction, regular feedback, and individualized course materials from expert teaching assistants.

Centrally located in Latin America, Uruguay is well-positioned to serve as a regional data science hub for its own citizens as well as neighboring countries Brazil, Argentina, and Chile. According to the World Bank, “Uruguay stands out in Latin America for being an egalitarian society and for its high income per capita and low level of inequality and poverty.” Uruguay rates high for most development indicators and is known for its well-developed social security, health, and educational systems.

“Our education partnerships are part of our commitment to advancing the global state of data science,” says IDSS director and professor of electrical engineering and computer science Munther Dahleh. “I’m pleased to be expanding our efforts with Plan Ceibal and the UTEC Program in Data Science. They’ve already had a big impact on education in Uruguay and Latin America.”

By combining their efforts, IDSS and the UTEC Program for Data Science can recreate much of the MIT classroom experience for learners at a distance — and at scale. The next cohort is set to begin in September.

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Source link : https://news.mit.edu/2020/idss-builds-educational-partnership-uruguay-0716 Author : Publish date : 2020-07-16 03:00:00 Copyright for syndicated content belongs to the linked Source .

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MIT Institute for Data, Systems, and Society builds educational partnership in Uruguay | MIT News

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