3 Short courses in Machine Learning in Italy

Theoretical Foundations of Machine Learning
In his three-course Johns Hopkins Engineering's Theoretical Foundations of Machine Learning Dr. Erhan Guven guides you through the full machine learning workflow: from how to clean and prepare data all the way to building deep learning neural networks.

Introduction to Machine Learning and Deep Learning in Geosciences
This is an introductory-level course of Machine Learning. The aim of this course is to provide an overview of the main machine learning methods and their application to geophysical, geochemical, geological and environmental data.

On Agriculture, Forest and Environmental Geodata Statistical Analysis, Modelling and Machine Learning [SAFEST]
This On Agriculture, Forest and Environmental Geodata Statistical Analysis, Modelling and Machine Learning [SAFEST] provides theoretical and practical teaching on statistical methods and tools for geodata handling and analysis, with special emphasis to soil traits, crop yield or plant biomass in agricultural, forest and other land uses under variable management and environmental conditions.