The course aims to introduce the mathematical and data analysis methods used in Geosciences and their implementation in Python. The main aim is to achieve an adequate mastery of these methods as well as the ability to develop and use the tools acquired for the study of physical processes involving the Earth system.
Curriculum
teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Author: Lin
An Introduction to Python Programming for Scientists and Engineers
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherAuthor: Lin
An Introduction to Python Programming for Scientists and Engineers
Type of delivery of the course
Lessons on the blackboard. Numerical exercises on the topics covered during the course in Python environment.Type of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course. teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Author: Lin
An Introduction to Python Programming for Scientists and Engineers
Mutuazione: 20410870 ANALISI DEI DATI NELLE GEOSCIENZE in Geologia e Tutela dell'Ambiente LM-74 R LAURO SEBASTIAN EMANUEL
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherAuthor: Lin
An Introduction to Python Programming for Scientists and Engineers
Type of delivery of the course
Lessons on the blackboard. Numerical exercises on the topics covered during the course in Python environment.Type of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course.