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Computational and Mathematical Engineering Stanford

Computational and Mathematical Engineering Stanford


Stanford University: Computational and Mathematical Engineering

Para inscribirse en unas Summer Sessions en Stanford University, debes seleccionar 2 cursos de Summer Sessions. A continuación puedes ver todos los cursos del área Computational and Mathematical Engineering; contenido y horario.

Recomendamos:
1.- Ver en que sesión (fechas y duración) se imparte cada uno de los cursos de esta área.
2.- Cuando sepas los cursos que más te interesan comprueba el horario para que no se solapen entre ellos.

DURACIÓN       FECHAS                       
8 semanas        June 23 – Agosto 19        
REQUISITOS:  Nivel Avanzado.
                                                                                                            


Cursos de Computational and Mathematical Engineering:

Computational and Mathematical Engineeringnº de créditosduración en semanas
Introduction to Probability and Statistics for Engineers3/48
Introduction to Scientific Computing3/48

Precios
 

CURSO Y ALOJAMIENTO DURACIÓN FECHASPRECIO
Summer Session 8 semanas. Jun 23 - Ago 19Desde 11.390,00 €

                                                                                                                                       

Descripción de los cursos:

Introduction to Probability and Statistics for Engineers

Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, non-parametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields.

Introduction to Scientific Computing

Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floating-point arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness.


 



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