FUNDAMENTALS OF MACHINE LEARNING FOR EARTH OBSERVATION BY NASA

Course Description
The Fundamentals of Machine Learning for Earth Observation course aims to equip learners with the essential knowledge and skills to leverage machine learning techniques for analyzing and interpreting Earth observation data. This course is designed for a diverse audience, including beginners, career changers, and professionals seeking to enhance their expertise in data analysis and remote sensing.

Participants will develop key competencies in machine learning algorithms, data pre-processing, and model evaluation, specifically within the context of Earth observation. The course will cover the following main topics:

Introduction to machine learning and its relevance to Earth observation
Data acquisition and pre-processing techniques for remote sensing
Supervised and unsupervised learning algorithms
Model evaluation and validation methods
Practical applications of machine learning in environmental monitoring and analysis
The course will be delivered through a combination of pre-recorded video lectures, supplementary online materials, interactive discussions, and hands-on assignments. Learners will be assessed through homework assignments, a capstone project, and will receive detailed feedback throughout the course.

Practical details include a flexible online format, with a duration of 8 weeks, and participants will receive certificates from both the EIT Deep Tech Talent Initiative and NASA upon successful completion.