Data Science and AI
How can we use data science to deliver societal impact?
Data Science for Social Good was established at the University of Chicago in 2013, and brought to UK in 2019 by the University of Warwick and the Alan Turing Institute.
It consists of an intense 12-week summer programme which trains high calibre data scientists to deliver research projects with positive social impact. Participants mostly work with charities and government organisations, and deliver usable open-source data products to support them to make a difference to the users they serve.
What makes a good project?
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Working with a charity or government organisation
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Data is currently available, or can be obtained
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The research will lead to actions that enhance social good
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Project completion is realistically achievable within 12 weeks.
Example projects
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Homeless Link: Automatic scanning of alerts to quickly identify rough sleepers most in need
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Ofsted: Early detection of problematic foster agencies
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World Bank: Identifying and analysing corruption risks in public administration
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Superintendencia Del Medio Ambiente (SMA): Prioritising environmental complaints
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ITU: Mapping the world's population.
What our project partners say
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“The DSSG experience has been amazing.” [Youlia Lozanova, ITU]
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“Great, skilledandhighly motivated participants - unbelievably helpful for all sides!“ [Sören Enkelmann, BMWi]
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“It has been a real privilege to work with DSSG.” [Juan Ardissone, DNCP]
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“It has been a wonderful experience for us and we highly recommend being part of this initiative to other organisations.” [Pablo Aguirre Hörmann, SMA]
What our students say
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“Working with DSSGxUKover the summer is an experience you do not want to miss.” [Cinny Lin]
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“DSSGx was an amazing experience. I learned a lot, made friends worldwide, and felt like I'm a part of something great.” [Amit Sasson]
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“I highly recommend this program to budding data scientists and students who want to work on projects that really matter.” [Prakhar Rathi]
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“The program was a highlight of my summer and I really gained so much from it.” [Tova Perlmann]
Principal Investigator: Dr Lyudmila Grigoryeva, Department of Statistics