MATLAB Tutorial

MATLAB is a programming platform used for mathematics, engineering and scientific computing. It provides built-in tools for calculations, visualization and application development. It simplifies complex tasks and provides a structured environment for problem-solving and analysis.

Basics

This section gives an overview of MATLAB, its main features and where it is applied.

• Introduction
• Features of MATLAB
• Applications of MATLAB

Installation

Here we will learn how to install MATLAB on different operating systems and set up the environment for use.

• On Windows
• On Linux
• On MacOS
• Setting Up the Environment
• Getting Started

Fundamental

Covers the fundamental building blocks of MATLAB:

• Variables
• Data Types
• Syntax
• Commands
• Symbolic variables
• Characters and Strings
• Classes and Object
• Tables

Matrices

MATLAB is built around matrices, this section explains how to work with matrices.

• Matrix
• Create a New Matrix
• Inverse of a Square Matrix
• Sparse Matrices
• Cosine Similarity Between Two Matrices

Functions

Explains different types of functions in MATLAB:

• Functions
• Creating Function
• User-Defined Functions
• Private Functions
• Function Inputs and Outputs
• Nested Functions
• Inline and Anonymous Functions
• Filter Function
• Function Handles
• Global Variables
• Error Handling

Control Flow and OOP

This section covers decision-making statements, looping constructs and object-oriented programming concepts used to structure and organize code.

• Conditional Statements
• Nested Switch
• Loops
• Break Statement
• Object Oriented Programming (OOP)
• Polymorphism

Plotting and Visualization

Focuses on creating 2D and 3D plots like charts and graphs to represent data visually.

• Plots
• 2D Plots
• 3D Plots
• Curve Fitting
• Annotation
• Pie Chart 
• Scatter Plot 
• Histogram 
• Bar Graph

Mathematics

Deals with mathematical computations such as trigonometry, calculus, differentiation, integration and polynomial handling.

• Trigonometric Functions
• Calculus
• Differentiation
• Integration
• Polynomials

Computation and Linear Algebra

Introduces algebraic computations including solving equations, working with eigenvalues and matrix transformations.

• Algebra
• Solving Linear Equations
• Reduced Row Echelon Form
• Eigenvalues and Eigenvectors
• Cayley-Hamilton’s Theorem

Differential Equations

This section shows how to solve differential equations using symbolic and numerical methods.

• Homogeneous Difference Equations
• Laplace Transform
• Fourier transform
• Differential Equation using Laplace Transform
• Method of Variation

Working with Image & Files

This section teaches how to process, analyze and edit images.

• Image Processing
• Edge detection
• Erosion of an Image
• Dilation of an Image
• Morphological operations
• Image shading
• MRI Image Segmentation
• Create Animated GIF Images
• Create Video From An Image
• Read Image File or Complex Image File
• Write Data to Text Files

Machine Learning

Introduces basic machine learning and deep learning concepts.

• Prediction Using Classification and Regression Trees
• Nearest-Neighbor Interpolation Algorithm
• Build Decision Tree
• K-Means Clustering
• Fuzzy C-means Clustering
• Deep Learning

Advanced Topics & Projects

Focuses on advanced tools and project-based learning.

• Simulink
• Simple App Using GUIDE
• Create Video From An Image
• App Building Components
• Creating Apps Using App Designer
• Top 10 Matlab Project Ideas