Learning

Applying Machine Learning to Atmospheric Science Data

Atmospheric Data Fundamentals → Applications in Weather Prediction

This advanced graduate-level path equips data scientists with the knowledge and skills to apply machine learning to atmospheric science data. It covers essential atmospheric data structures, statistical methods, and machine learning techniques for tasks like pattern recognition, clustering, and forecasting, with a focus on real-world applications such as weather prediction.