Supervised Machine Learning Readiness

 

Course Description

Supervised Machine Learning Readiness is a self-paced, beginner-friendly learning program designed for Earth Systems scientists to explore the core principles of supervised machine learning. This series uses a combination of step-by-step frameworks, exploratory widgets, and low-code exercises in Jupyter Notebooks, to explore the full cycle of machine learning model development. No programming experience is required. By the end of the series, you will be able to recognize when machine learning is an appropriate tool and critically evaluate machine learning in Earth systems science contexts.

 

Intended Audience

The lesson is intended for Earth Systems scientists, graduate and upper-level undergraduate students, and new and aspiring machine learning users. 

 

Course Access

You can access the course here (MetEd login required).

 

Questions or Comments? 

We welcome any comments or questions you may have regarding the content, instructional approach, or use of this lesson. Please e-mail your comments or questions to NSF Unidata Support (support AT unidata.ucar.edu). For technical support, please visit our Registration and Support FAQs: https://www.meted.ucar.edu/help