Modeling environmental systems (70897)
Models are one of the main tools for system investigation in earth and environmental sciences. In this course, the students learn what a model is, steps in model development, types of models, calibration and validation methodologies, and sensitivity and uncertainty analyses. Additional topics include spatial models, data-driven models, and numerical models.
Program
Earth Sciences
Degree
Master
Instructors
Machine learning in earth and environmental sciences (70938)
This course describes the fundamentals underlying machine learning and presents common methods in the field. The students learn the theoretical aspects of these methods and apply them for problem-solving in earth and environmental sciences. A major part of the course is devoted to supervised learning and deep learning methods and includes hands-on tutoring.
Program
Earth Sciences
Degree
Master
Instructors
Objective Methods of Data Analysis in the Earth Sciences (82653)
*Not offered during the 2019-2020 academic year* This course introduces many of the methods commonly used in the earth sciences to extract information from large datasets using objective, as opposed to subjective, methods. The goals of this course are to provide a working knowledge of the basic methods of objective analysis of meteorological, oceanographic, and…
Program
Atmospheric Sciences
Degree
Master’s
Instructors
Computational Models of Climate and Climate Change (82891)
*Not offered during the 2019-2020 academic year* This course provides an introduction to the science behind climate change, to the computational techniques used in constructing global climate models, and to the successes and failures of modern climate models. The course will also provide a historical perspective on climate modelling, from the early ENIAC weather simulations…
Program
Atmospheric Sciences
Degree
Bachelor’s