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Data science is a diverse field that combines statistics, data visualization, predictive modeling, and data analysis. Although there’s a variety of software tools and programming languages that allow you to work with one or more of these aspects, there are few that allow you to work with all of them. MATLAB is a powerful programming language and IDE that has an extensive set of features and capabilities.
When faced with complex data science tasks, there are several questions you should be asking throughout the various phases of your project. What is the best way to represent the data of interest? Is there anything unusual about the data distribution? Are the features in the data set highly correlated to an output or target of interest? What is the best way to model the data and system so that new data can be integrated without breaking the system?
In this MATLAB Intermediate course, you will discover how to use MATLAB for object-oriented programming. You will also learn the important relationship between data structures and classes, properties and objects, functions and recursion, and vectors and plotting. Finally, you will learn how to represent and visualize two-dimensional and three-dimensional vectors, and how to utilize the MATLAB apps for data science.
You will learn to use MATLAB for object-oriented programming, understand the relationship between data structures and classes, properties and objects, functions and recursion, and vectors and plotting, and how to represent and visualize 2D and 3D vectors and use the MATLAB apps for data science.
Yes. The course covers object-oriented design techniques in MATLAB, including classes, custom classes, objects, creating objects from classes, and the properties of classes and objects.
The course explains the difference between custom, anonymous, and recursive functions, with lessons on basic functions, anonymous functions, and recursive functions.
It covers data visualization techniques for multivariate data and assessing predictive classification models, with lessons on line and scatter plots, histograms and area plots, statistical analysis, predictive modeling, and model selection.
The course builds skills in MATLAB, object code, object-oriented programming language, object-modeling technique, object-oriented design, and object-oriented programming (OOP).