Natural Hazards The “Natural Hazards” course offers an in-depth exploration of the physical processes that drive natural and environmental risks, their historical impacts on human societies, and contemporary strategies for mitigation. Designed for students and a broad audience interested in understanding the science behind natural disasters, this course combines theoretical knowledge with...

Environmental History and the Human Factor The “Environmental History and the Human Factor” course explores the dynamic interactions between humans and their environment throughout history. It examines how societies have shaped and been shaped by their surroundings, focusing on the mutual influence between human actions and environmental changes. Designed for students and the wider audience interested...

Spatial Big Data analyses for environmental scenarios The “GIScience & Big Data” course offers an in-depth exploration of Geographic Information Science (GIScience) integrated with Big Data analytics to address spatial and temporal challenges. Designed for students and professionals interested in mastering cutting-edge tools and concepts, this course combines theoretical foundations with practical...

Advanced GIScience modeling The “Advanced Implementations of GIS” course provides a hands-on exploration of modern GIS (Geographic Information Systems) technologies, equipping students with the tools and knowledge to analyze and model spatial data effectively. Designed for students and professionals interested in mastering cutting-edge GIS applications, this course bridges theoretical understanding...

Python for Beginners is an online course tailored for students eager to dive into the world of Python programming. This course will guide you through the essentials of Python, from setting up and navigating Python environments to writing your first scripts. You will gain hands-on experience in scripting, explore the fundamentals of Object-Oriented Programming (OOP), and develop Python scripts using...

The Advanced Python Course is designed for students who have completed the Python for Beginners course (or equivalent) and wish to deepen their understanding of Python for spatial-temporal analysis of geographic data. Throughout the course, participants will learn to work with typical data structures, explore commercial and open-source packages for spatial data manipulation, and delve into advanced...