Machine Learning in Python for Environmental Science Problems

Participants will interact with real-world data and the ML pipeline through a series of Google Collaboratory notebooks that will enable thorough exploration of the data and methods. Participant understanding of the concepts will be reinforced with hands-on exercises at the end of each lecture that require implementing many of the techniques introduced while grappling with the challenges of real-world environmental datasets.

Day one will cover AI and ML fundamentals and introduce Python libraries commonly employed for data analysis, ML, and deep learning (DL). Day two will provide participants with the option of instruction on more advanced topics in ML/DL following a similar lecture/exercise format as employed on day one.

More information provided at the AMS AI Short Course website.