Data Science Climate Change

3 Credits · Level: Graduate, Undergraduate

Data Science, as a key component of Artificial Intelligence, is helping shape profound changes to society. An equally forceful phenomenon affecting our world is climate change. This course will investigate the myriad ways Data Science can be used to address climate change. This will include aspects of climate change which Data Science is already beginning to tackle, such as mitigating emissions from the five most carbon-intensive societal activities – energy, manufacturing, agriculture / land use, transportation, and buildings / infrastructure. We will also look at Data Science’s emerging role in areas such as climate modeling, biodiversity conservation, carbon capture, climate mitigation finance, geoengineering, climate ethics, and reducing the carbon footprint of Data Science itself. We will see how the following Data Science and Machine Learning topics can be used to address climate change: regression, gradient boosting, causal inference, interpretability, optimization, image processing, natural language processing, reinforcement learning, time-series analysis, and several neural network architectures. Using a variety of existing data sources, students will undertake a final project of their choosing to apply a Data Science technique to an aspect of climate change.