E.g., 2016-06-25
E.g., 2016-06-25
E.g., 2016-06-25
May 23rd 2016

An introduction to dynamical modeling techniques used in contemporary Systems Biology research. We take a case-based approach to teach contemporary mathematical modeling techniques. The course is appropriate for advanced undergraduates and beginning graduate students. Lectures provide biological background and describe the development of both classical mathematical models and more recent representations of biological processes. The course will be useful for students who plan to use experimental techniques as their approach in the laboratory and employ computational modeling as a tool to draw deeper understanding of experiments.

No votes yet
Mar 21st 2016

Ce cours contient les 7 premiers chapitres d'un cours donné aux étudiants bachelor de l'EPFL. Il est basé sur le livre "Introduction à l'analyse numérique", J. Rappaz M. Picasso, Ed. PPUR. Des outils de base sont décrits dans les 5 premiers chapitres. Les deux derniers chapitres abordent la question de la résolution numérique d'équations différentielles.

No votes yet
Feb 22nd 2016

Learn the basics of Finite Element Method (FEM), a numerical solution for structural analysis, and demonstrate its applications with MATLB and ANSYS.

No votes yet
Feb 1st 2016

Premiers pas dans MATLAB et Octave avec un regard vers le calcul scientifique

No votes yet
Nov 18th 2015

Utilización de la herramienta de software matemático MatLab para asignaturas de primer curso de Ingenierías.

Average: 9 (5 votes)
Nov 16th 2015

Investigate the flexibility and power of project-oriented computational analysis, and enhance communication of information by creating visual representations of scientific data.

Average: 1 (1 vote)
Nov 10th 2015

This MOOC explains how to model and simulate innovative ideas using MATLAB/Simulink and provides to you a number of methods suitable for modelling technical and economic systems and processes in a wide range of applications.

Average: 8.3 (10 votes)
Oct 19th 2015

Learn the fundamentals of digital signal processing theory and discover the myriad ways DSP makes everyday life more productive and fun.

No votes yet
Oct 5th 2015

This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals.

Average: 9 (3 votes)
May 1st 2015

Understanding how the brain works is one of the fundamental challenges in science today. This course will introduce you to basic computational techniques for analyzing, modeling, and understanding the behavior of cells and circuits in the brain. You do not need to have any prior background in neuroscience to take this course.

Average: 10 (1 vote)
Self Paced

This is an introductory course to Digital Signal Processing that can be taken at any time. The course deals with the fundamentals in addition to exploring techniques like filtering, correlation and Fourier analysis. There is an emphasis in applying DSP theory to practical problems.

Average: 4.1 (9 votes)
Jan 5th 2015

Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences.

No votes yet
May 26th 2014

En este curso vamos a aprender a escribir nuestros propios programas, usando software libre. Vamos a usar el lenguaje M, disponible en los paquetes MATLAB y Octave UPM, que son ampliamente usados en ciencias e ingeniería. No es necesario tener ningún conocimiento previo para seguir el curso, y al finalizar, habrás sido capaz de tomar las riendas de tu ordenador y escribir tus propios programas, incluso con gráficos sencillos.

No votes yet
Apr 6th 2014

This introduction to engineering course will help you learn modeling and analysis techniques for electrical, mechanical, and chemical systems and discover how engineered systems that seem very different are actually very similar.

No votes yet
Jan 21st 2014

This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.

No votes yet
Sep 4th 2013

This course is about learning to program well: building programs that are elegant, well tested and easy to maintain. The course is intended for students with no programming experience, but many former students who already knew how to program have said it made them better programmers.

No votes yet
Apr 8th 2013

In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

No votes yet
 

Tell your friends: