Data science for empowerment: understanding the data science training landscape for women and girls in Africa-Reference-Cited by-同舟云学术

Data science for empowerment: understanding the data science training landscape for women and girls in Africa

Published:2022-11-25 Issue:3 Volume:26 Page:437-462
ISSN:0971-8524
Container-title:Gender, Technology and Development
language:en
Short-container-title:Gender, Technology and Development

Author:

Babirye Claire¹,Muyoya Chisenga²,Mazumdar Suvodeep³^ORCID,Jimenez Andrea³,Maina Ciira⁴,Matogoro Jabhera⁵,Nyambura Ndung’u Margaret⁶,Kleine Dorothea²

Affiliation:

1. Artificial Intelligence Lab, Makerere University, Kampala, Uganda

2. Department of Geography, University of Sheffield, Sheffield, UK

3. Information School, University of Sheffield, Sheffield, UK

4. Centre for Data Science and Artificial Intelligence, Dedan Kimathi University of Technology, Nyeri, Kenya

5. Department of Computer Science and Engineering, The University of Dodoma, Dodoma, Tanzania

6. International Institute of Information Technology, Kenya

Publisher

Informa UK Limited

Subject

Development,Gender Studies

Link

https://www.tandfonline.com/doi/pdf/10.1080/09718524.2022.2137562

Reference97 articles.

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2. Adams, R., Fourie, W., Marivate, V. & Plantinga, P. (2020). Introducing the series: Can AI and data support a more inclusive and equitable South Africa?. Report for Policy Action Network (PAN).

3. Aduwo, J. R., Mwebaze, E. & Quinn, J. A. (2010). Automated vision-based diagnosis of Cassava Mosaic Disease, in Industrial Conference on Data Mining-Workshops (pp. 114–122). New York, NY.

4. Health at her fingertips: development, gender and empowering mobile technologies

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