Programming Techniques with MATLAB

26 ottobre 2015
26 October 2015

Location: Room A205 - Polo Scientifico Fabio Ferrari, Povo 1.

Free MATLAB seminar. This session is open to all professors, researchers and students.

During this seminar, you will get an update of recent capabilities in MATLAB, tips and tricks on how to design algorithms, how to efficiently access to your data from different data sources in MATLAB and how MATLAB is used for scientific computation in order to teach courses focused on mathematical modelling, statistics, optimization, financial modelling, programming, signal processing, etc.

Speaker Information:

Francesca Perino is a senior application engineer at MathWorks primarily focused on supporting customers in the finance industry. She also has a strong focus on mathematical modelling, High Performance Computing and application development fields. Before MathWorks, she spent few years working as research engineer and software developer. She holds a M.Sc. in Physics from Universita' degli Studi of Torino, with a major in numerical methods for dynamic atmospheric models and environmental analysis.

Agenda:

Time Title
  Welcome
10’ Introduction
In this session we will go over how you can have access to the tools and why MATLAB is an important skill to have on your CV
40’  Programming Techniques in MATLAB
In this session, you will gain some insights on how you can program in MATLAB efficiently.
In recent versions, MATLAB introduced several new programming concepts, including new function and data types. You will learn how using the right function and/or data type can lead to more robust and maintainable code.
Demonstrations will show you how to apply these techniques to problems that arise in typical applications.
60’

Tackling Big Data with MATLAB

In this session, you will learn strategies and techniques for handling large amounts of data in MATLAB. Topics covered include:

  • Using best practices for memory use in MATLAB
  • Accessing data in large text files, databases or from web services
  • Leveraging distributed memory to work with large data sets