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Challenge

Artificial Intelligence: Predict SDG indicators from publicly available data

The big idea: use country data over the years to identify

what factors influence a SDG

Challenge type: Mini (4 weeks)

Challenge owner: Universidade Aberta

Facilitator: José Coelho, Vitor Rocio

Facilitator Contact data: jose.coelho@uab.pt,

vitor.rocio@uab.pt

Challenge is related to the topic of Artificial Intelligence

 

 

Context & relevance: in general relating to SDG / specific to a field of vocational application

This challenge is completely related to SDG, but not specific to a field of application. Students may choose a SDG according to their preference or labour context, studying their depending factors and producing recommendations for countries and companies. The focus is on ML techniques applied to past data.

 

Variants of the challenge

N/A - each student can select a SDG and target indicator, so the challenges may be very different, but solved with similar techniques

 

Business partner in an industry or a research field

N/A

Prerequisites of the learners

Functional requirements

Software: R language 

Hardware: N/A

Working Space:  The R Project for Statistical Computing

Impact

Production of sets of recommendations for public bodies/companies in order to improve the identified SDG, based on ML findings.

Open Issues and questions

Indicators that the ML techniques do not prove to influence the SDG may be reported as irrelevant, but it is not clear how that can be reflected on the recommendations.

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ASSISTANT -
Challenge Based Learning in AI Enhanced Digital Transformation Curricular 
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