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African-Countries-SDG-Predictive-Model

AI Statistical Prediction Model for Africa’s rate of Employment in Agriculture with respect to Education Attainment, Literacy Levels, employment and unemployment rate towards boosting Gross Domestic Product(GDP).

Unemployment has been a persistent challenge for the African youth over the past 15 years where many African youths are seeking white-collar jobs and ignoring the informal jobs sectors and yet, the truth is that a large number of the population still dwell in the informal sectors specifically Agriculture [4]. Despite the informal sector, specifically, agriculture, becoming an important source of employment and the backbone of most economic activities in African countries, these informal jobs in agriculture still are not contributing enough towards boosting the African economy and consequently increasing the African GDP growth rate. Our core objective is to create a solution in the form of an AI model that predicts the growth or decline rate of the total number of employees in the informal sector(in this case agricultural sector) and how that correlates with factors such as levels of education, literacy levels and annual Growth Domestic Product(GDP) of African Countries.

Objectives

  • Identify a sustainable development challenge in Africa i.e how the rate of Agriculture unemployment in Africa affects the annual GDP of African countries.
  • Develop an AI-based solution to the identified problem from an AI and Data Science Analysis.
  • How viable can the proposed solutions be commercialized?
  • Documenting the problem identification and solution process.
  • Building a strong solution and recommendation to the problem.

Links to resources and Documentations.

Authors and Contributors

  • Zubeir Msemo
  • Jaochim Wambua
  • Collins Nnamuka
  • Ephraim Adongo

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