Predicting Air Pollution Levels in Mexico Using AI

This Omdena Local Chapter Challenge runs for 4 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Mexico City, Mexico Chapter.

The problem

The specific problem that this project aims to solve is to develop machine learning models that can predict air pollution levels in different parts of the city based on various factors such as weather data, traffic patterns, and industrial activity.

The goals

By providing more accurate and timely information on air pollution levels, the project can help policymakers and community leaders to make more informed decisions about policies and interventions to reduce air pollution in the city.

This project aims to leverage the power of data and AI to better understand and potentially predict air pollution levels in Mexico City. Doing so, it can help inform policy decisions, raise public awareness, and ultimately reduce air pollution levels in the city.

The project also has the potential to make a significant positive impact on public health and the economy. Reducing air pollution, it can improve the quality of life for residents, reduce healthcare costs, and increase productivity.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work