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An Initiative for Prevention Education and Research in Latin America

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Eric C. Brown¹, Francisco Cardozo¹, Maria Fernanda Reyes²

[!IMPORTANT]

This project was developed with the support of the Expanding the Use of Collaborative Data Science at UM initiative during the Fall of 2023 by the Frost Institute for Data Science and Computing (IDSC) at the University of Miami.

Background 💡

While the United States has seen substantial growth in the application of Machine Learning techniques in public health, Latin America presents an untapped opportunity for expansion. This project aims to capitalize on this potential by harmonizing and sharing Machine Learning methodologies in the region, thereby fostering scientific inclusively and enhancing prevention science in Latin America.

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Objectives

1. To adapt Machine Learning teaching materials to be culturally and linguistically appropriate for Latin American researchers.
2. To disseminate these methodologies through academic and research collaborations.

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Partners ♦️

• Nuevos Rumbos Corporation
• Colombian Institute for Education and Evaluation (ICFES)
• University of Los Andes
• Fundación Universitaria Konrad Lorenz
• Universidad Nacional de Colombia

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Code of Conduct ‼️

This project is governed by the Code of Conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to Eric C. Brown.

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Workshops Materials

Workshop website

Contributing ♥️

We welcome contributions to this project. Please read our CONTRIBUTING guide for details on the process for submitting pull requests to us.

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License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Footnotes

1. University of Miami, Miller School of Medicine, Department of Public Health Sciences. ↩ ↩²

2. Universidad de los Andes. Facultad de Ciencias Sociales. Departamento de Psicología.. ↩