MATLAB is a brilliant software to help design the GUIs for your apps. It is commonly used by analysts, scientists and programmer to create apps for their programs. MATLAB offers two amazing different utilities to help you create different Graphical User Interfaces. These two utilities are GUIDE and App Designer.
The GUIDE provides essential graphical components for converting your code into a meaningful software. The graphical components include radio buttons, tables, check boxes, sliders and many others.
The App Designer is a next-generation tool for creating and designing apps in MATLAB. The App Designer includes many new design components that were previously absent in MATLAB’s GUIDE. The essential beauty of App Designer is the integration of the two task of coding and designing in creating apps. It makes this possible with its new editor. This segment is designed so that a MATLAB programmer can easily transform his code to a beautiful User Interface and app.
If you want to learn how to design GUIs with this amazing tool, then you’ve got the right course! We use a hands-on approach to help you learn the basics as well as the practical applications of using both tools to design a sample project with both tools.
The first segment will completely go over GUIDE, while the second segment includes a detail lesson on App Designer.
What you will learn in this course:
Section 1: Basics of the GUIDE Linking the Code with GUI Advance Techniques for GUIDE Sample Projects with GUIDE More Useful Tricks and Examples with GUIDE
Section 2: Basics of App Designer Tips and Tricks for Effective use of App Designer Coding GUI's Advance Techniques Sample Projects with App Designer
Enroll now and become a master in MATLAB with our hands-on and detailed course!
About the Instructor
I am Dr. Nouman Azam and i am Assistant Professor at the Department of Computer Science, National University of Computer and Emerging Sciences.I had over a decade of experience in research and teaching.
My research work is mainly on the exploration of machine learning techniques in application areas such as bioinformatics, text summarization, text categorization, email filtering, security, recommender systems and medical decision making. On theoretical side, i am interested in applying the theories of rough sets, game theory, optimization and conflict analysis to machine learning tasks. For my Masters thesis, i applied different machine learning techniques to select important features in spam email filtering. For my doctoral thesis, i investigated the applications of machine learning techniques such as rough sets, game theory, genetic algorithms, gradient descent and others to learn and extract data patterns. In the recent past, I taught many machine learning related courses at the undergraduate and graduate levels.
MATLAB remained my number one choice for implementing ideas and converting my code to meaningful softwares. I implemented all the code of my Masters and Doctoral thesis in MATLAB.
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