Extreme heat poses major threats to human and environmental health and safety. In this workshop, you use Amazon SageMaker AI and open data from Amazon Sustainability Data Initiative (ASDI) to uncover patterns in vegetation and temperature, understand risks to urban areas, and simulate solutions that reduce risk to communities.

In particular, you will:
- Investigate the relationship among temperature, vegetation, and other environmental factors (such as water and soil build-up) using Amazon SageMaker Studio
- Gain hands-on experience working with geospatial data using AWS services
- Learn about the Amazon Sustainability Data Initiative (ASDI) to access open satellite imagery data (USGS Landsat)
- Build and deploy a machine learning model to simulate more sustainable outcomes (less heat risk)

This workshop is aimed at individuals who want to learn how Artificial Intelligence and Machine Learning can help make predications based on open source data, individuals who want to experiment with the power of satellite imagery, as well as individuals who want to on-ramp to cloud-native geospatial workflows. No specific background knowledge is required. This workshop provides step-by-step instructions along with the code required to run each step. Participants can also elect to make additional, optional coding improvements.