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MATLAB Programming Simulink

Beginner to Pro with ChatGPT

Farhan Anwar | 100k Students | MATLAB Programming and CST Course

Comprehensive MATLAB Programming and App Development Course

This MATLAB Programming and App Development course is a complete guide for beginners and professionals who want to master MATLAB's capabilities in programming, data visualization, and app creation. The course starts with an introduction to MATLAB, covering the environment, command window, workspace, editor, and file navigation. Students will learn how to create variables, explore data types, perform type casting, and manage matrices and vectors efficiently.

Read more

Comprehensive MATLAB Programming and App Development Course

This MATLAB Programming and App Development course is a complete guide for beginners and professionals who want to master MATLAB's capabilities in programming, data visualization, and app creation. The course starts with an introduction to MATLAB, covering the environment, command window, workspace, editor, and file navigation. Students will learn how to create variables, explore data types, perform type casting, and manage matrices and vectors efficiently.

Matrix operations are at the core of MATLAB, and this course delves into matrix indexing, concatenation, and advanced functions like inverse, determinant, and row reduction. You'll also explore MATLAB's powerful plotting features, including 2D and 3D plots, continuous and discrete data visualization, and creating high-resolution (600 DPI) graphs for professional presentations.

The course emphasizes data integration by teaching how to import and export data as MAT, CSV, text, and image files. You'll also learn to work with videos and directly integrate datasets into MATLAB for analysis.

Control flow topics, including conditional statements (IF-ELSE, SWITCH-CASE) and loops (FOR, WHILE), are thoroughly covered, enabling you to write dynamic and efficient code. Additionally, the course includes creating user-defined functions to build custom solutions.

In the advanced section, you'll learn to use MATLAB's App Designer to build interactive applications. This includes creating GUIs, adding callback functions, debugging, and packaging standalone apps for PC installation.

By the end of this course, you’ll have a strong foundation in MATLAB programming, data visualization, and app development, equipping you to tackle real-world engineering, scientific, and data science problems. Whether you're a student, researcher, or professional, this course will empower you to leverage MATLAB for maximum impact.

Enroll now to unlock the full potential of MATLAB programming and app development.

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What's inside

Learning objectives

  • Master matlab basics: students will gain proficiency in navigating the matlab environment, managing variables, and performing matrix and vector operations.
  • Perform data visualization: learn to create high-quality 2d and 3d plots, continuous and discrete visualizations, and export professional-grade graphs.
  • Design interactive apps: create guis in matlab’s app designer, add callbacks, debug, and package standalone apps for seamless distribution.
  • Develop matlab applications: build custom user-defined functions, work with loops and conditional statements, and integrate data for real-world problem-solving.

Syllabus

Introduction to MATLAB: Master the Basics of Programming and Simulation
Introduction to MATLAB: Learn the Basics of Programming and Technical Computing
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Exploring the MATLAB Environment: Mastering the Command Window Basics
MATLAB Environment: Command Window Demo for Hands-On Learning
MATLAB Environment: Understanding and Managing the Workspace
MATLAB Environment: Mastering the Editor Window
MATLAB Environment: Navigating and Utilizing the Current Folder
Understanding MATLAB Variables
Creating MATLAB Variables: A Step-by-Step Guide
Exploring Data Types in MATLAB
Type Casting in MATLAB: Converting Data Types with Precision
Working with 3D Matrices in MATLAB: Manipulation and Visualization
Matrices in MATLAB: Fundamentals and Advanced Operations
Matrix Indexing in MATLAB: Accessing and Manipulating Data
Essential MATLAB Functions for Matrix Operations
Useful Functions for Matrix Operations in MATLAB
Vectors in MATLAB: Creation, Operations, and Applications
Matrix Operations in MATLAB: A Comprehensive Guide to Mathematical
Colon Operator in MATLAB: Simplifying Matrix and Array Operations
Element-by-Element Operations in MATLAB: A Detailed Guide to Array Calculations
Linear and Logical Indexing in MATLAB: Efficient Data Selection and Manipulation
Matrix Concatenations in MATLAB: Combining and Building Matrices
Matrix Operations in MATLAB: Inverse, Determinant, and Row Reduction (rref)
Matrix Operations in MATLAB: Mathematical and Computational Techniques
Import and Export Data in MATLAB: Seamless Data Integration and Management
Exporting Data in MATLAB: Save as MAT and CSV Files
Exporting Images in MATLAB: Save Graphics as PNG Files
Exporting Tables in MATLAB: Save Data as TXT and CSV Files
Direct Data Import in MATLAB: Simplify Data Integration
Importing Text Files in MATLAB: Step-by-Step Guide for Data Handling
Loading Data in MATLAB: Converting to Matrix and Table Formats
Loading Images into MATLAB: A Guide to Image Processing and Analysis
Loading Video Files into MATLAB: A Step-by-Step Guide for Video Processing
2D Plots in MATLAB: Visualizing Data
3D Plots in MATLAB: Visualizing Data in Three Dimensions
Continuous and Discrete Plots in MATLAB: Techniques for Data Visualization
Creating High-Quality Plots in MATLAB: Tips for Professional Visualizations
Generating High-Resolution Plots in MATLAB: Achieving 600 DPI
Importing Data into MATLAB and Creating Informative Plots
Combining Graphs in MATLAB: Merging Multiple Plots into a Single Figure
Graphs and Plots in MATLAB: A Comprehensive Guide to Data Visualization
Creating Subplots in MATLAB: Displaying Multiple Plots in a Single Figure
Conditional Statements in MATLAB: Control Flow for Dynamic Programming
IF-ELSE-END Statements in MATLAB: Implementing Conditional Logic
IF-ELSEIF-ELSE-END in MATLAB: Advanced Conditional Statements
IF-END Conditional Statement in MATLAB: Simplifying Decision-Making
SWITCH-CASE Conditional Statement in MATLAB: Streamlining Multi-Choice Logic
Loops and Conditional Logic in MATLAB: Automating Repetitive Tasks
For Loop in MATLAB: A Guide to Iterative Programming
Nested For Loops in MATLAB: Mastering Multi-Level Iterations
While Loop in MATLAB: Efficient Control for Repetitive Tasks
User-Defined Functions in MATLAB: Building Custom Solutions
Creating Functions with No Output in MATLAB: Simplifying Task Automation
MATLAB Function Example: Building and Using Custom Functions
User-Defined Functions in MATLAB: Creating Customized Programming
User-Defined Functions with Direct Input in MATLAB: Streamlining Function Calls
App Designer in MATLAB: Building Interactive Applications
Introduction to App Designer in MATLAB: Creating Interactive User Interfaces
Building a Calculator GUI App in MATLAB App Designer
Creating a Simple GUI in MATLAB: Draw a Graph with a Push Button Click
Adding Callback Functions to Number Buttons in MATLAB App Designer
Adding Functions to Operator Buttons in MATLAB App Designer
Debugging the Calculator App in MATLAB: Identifying and Fixing Errors
Creating an Add-On App in MATLAB App Designer: Enhancing Functionality
Creating and Installing a Standalone App in MATLAB

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers matrix operations, data visualization, and app development, which are essential for technical computing and align with the needs of engineers, scientists, and data analysts
Teaches how to create high-quality 2D and 3D plots and generate high-resolution graphics, which are useful for professional presentations and publications
Explores MATLAB's App Designer for creating GUIs, adding callback functions, and packaging standalone apps, which is valuable for developing interactive tools and applications
Explains how to import and export data in various formats (MAT, CSV, text, image, video), which is crucial for integrating real-world datasets into MATLAB workflows
Details how to create user-defined functions, work with loops and conditional statements, and build custom solutions, which are essential for automating tasks and developing custom algorithms
Starts with an introduction to MATLAB, covering the environment, command window, workspace, editor, and file navigation, which builds a strong foundation for beginners

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in MATLAB Programming Simulink: Beginner to Pro with ChatGPT with these activities:
Review Linear Algebra Fundamentals
Reinforce your understanding of linear algebra concepts, particularly matrix operations and vector manipulation, which are crucial for effective MATLAB programming.
Browse courses on Linear Algebra
Show steps
  • Review matrix operations such as addition, subtraction, multiplication, and inversion.
  • Practice solving systems of linear equations using matrices.
  • Familiarize yourself with vector spaces and linear transformations.
Study 'MATLAB for Engineers' by Holly Moore
Enhance your understanding of MATLAB's application in engineering by studying a textbook that focuses on practical examples and case studies.
View MATLAB for Engineers on Amazon
Show steps
  • Read the chapters relevant to your engineering discipline.
  • Work through the examples provided in the book.
  • Apply the concepts learned to solve engineering problems.
Read 'Mastering MATLAB' by Duane Hanselman and Bruce Littlefield
Deepen your understanding of MATLAB syntax, functions, and programming techniques by studying a comprehensive MATLAB reference book.
View Mastering MATLAB on Amazon
Show steps
  • Read the chapters relevant to matrix operations, data visualization, and app development.
  • Work through the examples provided in the book to reinforce your understanding.
  • Use the book as a reference while completing the course assignments.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Complete MATLAB Coding Challenges
Sharpen your MATLAB programming skills by solving coding challenges that focus on matrix manipulation, data visualization, and algorithm implementation.
Browse courses on MATLAB
Show steps
  • Find online resources that offer MATLAB coding challenges.
  • Solve at least three coding challenges per week, focusing on different aspects of MATLAB programming.
  • Review your solutions and compare them with the solutions provided by others.
Create a MATLAB Tutorial Video
Solidify your understanding of a specific MATLAB topic by creating a tutorial video that explains the concepts and demonstrates their application.
Browse courses on MATLAB
Show steps
  • Choose a MATLAB topic that you want to teach, such as matrix operations or data visualization.
  • Prepare a script and examples to demonstrate the topic.
  • Record a video tutorial explaining the concepts and demonstrating the examples.
  • Edit the video and upload it to a video-sharing platform.
Develop a Data Analysis Tool in MATLAB
Apply your MATLAB skills to create a practical data analysis tool that can process and visualize real-world datasets.
Browse courses on Data Analysis
Show steps
  • Choose a dataset to analyze, such as stock market data or weather data.
  • Write MATLAB code to import, clean, and process the data.
  • Create visualizations to present the data in a meaningful way.
  • Add interactive features to the tool using MATLAB's App Designer.
Contribute to a MATLAB Open Source Project
Gain practical experience and contribute to the MATLAB community by participating in an open-source project.
Browse courses on MATLAB
Show steps
  • Find a MATLAB open-source project on platforms like GitHub.
  • Review the project's documentation and code.
  • Identify areas where you can contribute, such as bug fixes or new features.
  • Submit your contributions to the project.

Career center

Learners who complete MATLAB Programming Simulink: Beginner to Pro with ChatGPT will develop knowledge and skills that may be useful to these careers:
Research Scientist
A research scientist often uses software to conduct experiments, and the MATLAB skills developed in this course are directly applicable to research-oriented roles. This course enables future research scientists with the ability to perform matrix operations, analyze data, generate high-resolution plots, and create custom functions to automate research tasks. The knowledge gained will be helpful for data analysis and interpretation as well as for presenting results in professional settings. The course's coverage of data import and export can be especially useful for integrating data from various sources. A research scientist may also find the app design useful for developing research tools.
See salaries and explore the career path for Research Scientist
Simulation Engineer
A simulation engineer creates models to simulate real-world systems, and by taking this course, one can develop skills in MATLAB which are helpful for building simulations. The course will allow a simulation engineer to manipulate data, perform complex calculations using matrices and vectors, and visualize results. The knowledge gained will be helpful for modeling dynamic systems and performing simulations. This course's teachings about creating custom functions can aid in building modular simulation components. This course can help a simulation engineer build and debug models for many different types of simulations.
See salaries and explore the career path for Simulation Engineer
Data Scientist
A data scientist leverages programming skills to analyze complex data, and this course will help one build a foundation in MATLAB, which is commonly used in data science for numerical analysis and algorithm development. The course covers data import, export, manipulation, and visualization, all of which are crucial for a data scientist. These skills will help one process datasets effectively, perform statistical analyses, and create meaningful visualizations. The course also provides a foundation for developing custom functions, which could improve data analysis pipelines. A data scientist may find the app development and debugging sections beneficial to producing interactive data tools.
See salaries and explore the career path for Data Scientist
Control Systems Engineer
A control systems engineer designs and analyzes systems to control processes, and a course like this one will be helpful for modeling and simulating these systems using MATLAB. The matrix operations, plotting, and data handling taught in this course can assist with the design and analysis of control systems. The course's focus on creating user-defined functions will be beneficial for developing custom algorithms and simulations. A control systems engineer may find the app development section relevant for building user interfaces for controlling and monitoring systems.
See salaries and explore the career path for Control Systems Engineer
Software Engineer
A software engineer develops applications and systems, and the programming, debugging, and app development skills learned in this course are very applicable to this role. This course teaches the fundamentals of programming in MATLAB, which can be useful for developing software tools and scripts needed in many engineering and scientific settings. The app development section can also be directly used to design custom interfaces and software. This course's focus on data handling and visualization might be helpful for software engineers working on data-driven applications. A software engineer may find the debugging section particularly valuable for creating reliable tools.
See salaries and explore the career path for Software Engineer
Mechanical Engineer
A mechanical engineer designs, analyzes, and manufactures mechanical systems. This course's coverage of matrix operations, data visualization, and simulation capabilities in MATLAB are very useful for many mechanical engineering tasks. This course will help a mechanical engineer to model and simulate mechanical systems. The course's coverage of conditional statements, loops, and functions will help automate calculations. A mechanical engineer can use the App Designer skills to develop custom tools for design and analysis. The practical training in data handling will enable better analysis of experimental data.
See salaries and explore the career path for Mechanical Engineer
Aerospace Engineer
An aerospace engineer works with aircraft and spacecraft, and the skills learned in this course are helpful for simulating and analyzing aerospace systems. This course teaches MATLAB, which is widely used for aerospace engineering analysis and modeling. The course's coverage of linear algebra, matrix manipulations, data visualization, and custom function development helps an aerospace engineer to model flight dynamics and perform simulations. The ability to import and export data will be helpful for incorporating experimental data into models. An aerospace engineer will also find that the app design skills are useful for developing tools to perform calculations or simulations.
See salaries and explore the career path for Aerospace Engineer
Biomedical Engineer
A biomedical engineer applies engineering principles to healthcare, and this course's training in MATLAB is useful for data analysis and modeling of biological systems. This course's coverage of data import, export, and visualization will aid in handling and presenting biomedical data. The course teaches how to perform matrix operations, data manipulation, and custom function creation, all of which are helpful for working with biomedical datasets. A biomedical engineer, for example, can use this course to develop simulation tools. The app development component will also be useful for developing custom biomedical tools.
See salaries and explore the career path for Biomedical Engineer
Robotics Engineer
A robotics engineer designs and builds robots, and this course develops skills essential for simulating and controlling robotic systems. This course covers matrix operations, data visualization, and app development, which are all important for this robotics. The course will allow a robotics engineer to more easily process sensor data, visualize motion, and design control systems. The material on custom function creation will be helpful for building modular robotics applications. A robotics engineer might leverage the knowledge of App Designer to develop user interfaces for controlling robots.
See salaries and explore the career path for Robotics Engineer
Quantitative Analyst
A quantitative analyst, or quant, uses mathematical and statistical methods for financial analysis. This course's focus on MATLAB makes it useful for a quant who will likely use programming to handle large quantities of data. By taking this course, a quantitative analyst will learn to import, export, and manipulate datasets, create visualizations, and develop custom functions. These lessons can help a quantitative analyst to perform complex calculations and analysis of financial data. The knowledge of conditional statements and looping will allow one to create programs and scripts, which is a key job function for a quant. The app design may also be useful for rapid prototyping of tools.
See salaries and explore the career path for Quantitative Analyst
Image Processing Engineer
An image processing engineer works with visual data, and this course helps develop a foundation in MATLAB, which is commonly used for image processing tasks. The course covers data import and export, as well as direct loading of images, which would be helpful for one who works with image data. The course also covers data visualizations, which would be helpful when analyzing and presenting images. The ability to create custom functions will help an image processing engineer to build image processing routines. An image processing engineer can apply what they learn to develop image enhancement and analysis tools.
See salaries and explore the career path for Image Processing Engineer
Process Engineer
A process engineer designs and improves manufacturing processes, and this course will enable one to simulate and analyze process data. The course's approach to data handling, plotting, and custom function creation is very useful for modeling and optimizing industrial processes. A process engineer will be better equipped to analyze data, visualize trends, and develop tools to improve process efficiency. The skills in this course will help a process engineer to understand and optimize manufacturing operations. A process engineer will likely use the app design to make custom tools.
See salaries and explore the career path for Process Engineer
Signal Processing Engineer
A signal processing engineer analyzes and manipulates signals, and this course helps build skills for signal analysis using MATLAB's programming environment. By taking this course, a signal processing engineer will learn to process data, perform computations using matrices and vectors, and create visualizations of signals. The course's coverage of data importing and exporting will be beneficial for processing various forms of signal data. The ability to develop custom functions will improve a signal processing engineer's capacity to build custom algorithms. A signal processing engineer can use these skills to design filters, analyze spectral data, and process audio and sensor signals.
See salaries and explore the career path for Signal Processing Engineer
Algorithm Developer
An algorithm developer designs and implements algorithms and the course helps build a strong foundation of programming skills necessary for algorithm development in MATLAB. This course's coverage of conditional statements, loops, and user-defined functions will help one to write and test algorithms. The data handling and matrix manipulation techniques will aid in implementing and testing algorithms on numerical data. The skills in data visualization will be helpful in analyzing algorithm performance . An algorithm developer may use this course as training for implementing and testing complex algorithms.
See salaries and explore the career path for Algorithm Developer
Financial Analyst
A financial analyst examines financial data and the course enhances numerical computation and data analysis skills, which are useful for financial modeling and analysis. This course's exploration of matrix operations and data handling can enable a financial analyst to perform calculations with financial data. The data visualization and plotting will be helpful for presenting findings. A financial analyst will be able to create financial models and tools by writing custom functions from this course. A financial analyst may find the course helpful for handling and presenting large volumes of financial data.
See salaries and explore the career path for Financial Analyst

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in MATLAB Programming Simulink: Beginner to Pro with ChatGPT.
Cover image
Mastering MATLAB
Save
Comprehensive guide to MATLAB, covering a wide range of topics from basic syntax to advanced programming techniques. It serves as an excellent reference for understanding MATLAB's functionalities and applying them to various engineering and scientific problems. It is commonly used as a textbook in universities and by industry professionals. This book provides additional depth to the course by offering detailed explanations and examples of MATLAB's capabilities.
Mastering MATLAB
Paperback
Check
Mastering MATLAB
Kindle Edition
Check
MATLAB for Engineers
Save
Provides a practical introduction to MATLAB for engineering students. It covers the fundamentals of MATLAB programming, data analysis, and visualization. It useful reference for understanding the application of MATLAB in solving engineering problems. This book adds breadth to the course by providing real-world examples and case studies.
MATLAB for Engineers
Paperback
Check
MATLAB for Engineers
Kindle Edition
Check

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Effort
8.5 total hours
Via
Udemy
Instructor
Farhan Anwar | 100k Students | MATLAB Programming and CST Course
Language
English
Good to know
Covers matrix operations, data visualization, and app development, which are essential for technical computing and align with the needs of engineers, scientists, and data analysts
Teaches how to create high-quality 2D and 3D plots and generate high-resolution graphics, which are useful for professional presentations and publications
Explores MATLAB's App Designer for creating GUIs, adding callback functions, and packaging standalone apps, which is valuable for developing interactive tools and applications
Explains how to import and export data in various formats (MAT, CSV, text, image, video), which is crucial for integrating real-world datasets into MATLAB workflows
Details how to create user-defined functions, work with loops and conditional statements, and build custom solutions, which are essential for automating tasks and developing custom algorithms
Starts with an introduction to MATLAB, covering the environment, command window, workspace, editor, and file navigation, which builds a strong foundation for beginners
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