As statistics and machine learning methods become more pervasive, policymakers have also increased their use of these techniques when deciding how to allocate public resources. In this project, you will analyze economic and social development indicators for 22 provinces of Argentina to help plan an education program.
This project assumes you can manipulate data frames using
ggplot2, and understand principal component analysis (PCA) and
k-means clustering. You can learn these skills from
DataCamp's Introduction to the Tidyverse and
Unsupervised Learning in R.
The data for this project was published by INDEC and includes indicators such as poverty, population, and GDP for each province.
Data Scientist at Transforma Uruguay
With a background in economics, Rafael works as a data scientist at Transforma Uruguay, assessing the impact of public policy in the welfare of the citizens of Uruguay.See More