Training - Courses

MLPR: MATLAB Programming Techniques

This one-day course provides hands-on experience using the features in the MATLAB language to write efficient, robust, and well-organized code. These concepts form the foundation for writing full applications, developing algorithms, and extending built-in MATLAB capabilities. Details of performance optimization, as well as tools for writing, debugging, and profiling code, are covered. Topics include:

Programming for robustness
Structuring code
Structuring data
Classes and objects

Note: A 1 hour test session will be scheduled one day prior to the first day of class. This session is to verify that the visual and audio connection is working properly on your computer. The required product software should be installed for the test session. It is highly recommended that you attend this session to ensure a successful and timely class start.

VIEW SCHEDULE and Register SHARE with Manager/Colleague

	Detailed course outline

Day 1 of 1
Programming for Robustness	Objective: Create robust applications that withstand unexpected input and produce meaningful errors. Use built-in MATLAB functions and programming constructs, and employ standard techniques for handling error conditions. Explore tools for debugging code, diagnosing problems, and measuring performance. Warnings and errors Handling errors The try-catch construct The MException object MATLAB Code Analyzer Directory reports MATLAB Debugger Assessing performance MATLAB Profiler
Structuring Code	Objective: Modularize code into readable and maintainable functions. Explore the different function types available in the MATLAB language and the tradeoffs associated with each type. See how function type affects performance and reliability of the code. Private functions Subfunctions Nested functions Function handles Precedence rules Comparison of function types
Structuring Data	Objective: Explore choices for storing data within a MATLAB application and how they affect the application's storage requirements and execution time. Use common techniques for improving performance when storing, accessing, and processing data. Cell arrays Structure arrays Other data containers Preallocation Vectorization Memory management Passing data between functions
Classes and Objects	Objective: Combine data and its associated operations into a custom data type, or class. Write classes and create objects from those classes. Organize large applications using custom classes. Class definition files Properties Property attributes Methods Creating object instances Handle classes Overloading operators Precedence rules

Prerequisites

MATLAB Fundamentals

Course Length - 1 day