MATLAB

A MATLAB software training outline generally follows a structured path from basic to advanced skills. Standard programs start with the user interface and data handling, then move into coding logic, and end with real-world applications.

Phase 1: Beginner/ Basics

  • MATLAB Environment & Interface:
  • Command window, current folder, workspace and command History
  • Creating and managing live scripts

 Data Types and Variables

  • Naming rules, assigning values and clearing workspace data.
  • Numeric types,( double, integers), characters, strings and logical ( Boolean)values.

 vectors and Matrices:

  • Creating arrays using brackets [], colon operators and linespace().
  • Matrix dimensions, transposing (‘ ), and indexing/slicing matrix elements.

 Basics Math & Operation:

  • Arithmetic operation and built-in math functions ( log, exp, sqrt. Trigonometrics
  • Element-wise operations using the dot operator ( .*-^) versus linear algebra matrix muiltiplication(*).

Data Visualization 2D:

  • Basics 2D line plots , scatter plot, adding tittle blocks, lables, legenda and grid lines.

Phase 2: Intermediate/core programming

          Control Flow & logic:

  • Conditional statements ( if, elself ,else).
  • Loop ( for loops while loops ) error handling.

 

Writing custom Functions:

  • Function syntax, input/output, arguments, local versus global variables, and anonymous functions.

 

 

 

Avanced data Structures :

  • Cell arrays, structures, tables and timetable for mixtures, tables and time table for mixed data organization.
  • Data import & export :
  • Reading and writing data from/to external files ( CSV) excel spread sheets
  • Data Intermediate Data Analysis & plotting :
  • Statistical analysis, (mean,median,standard deviation, and data interpolation.
  • Advance 3D visualization,(mesh,surf,plot, contour plot,subplot layouts)

Phase 3: Advance Topics

  • Symbolic Math & Calculus :
  • Defining symbolic variables, solving algebraic equations, analytically, and performing symbolic integration and differentiation.

Optimizing code performance :

  • Vectorization techniques to eliminate slow loops, profiling code excecution, and pre-allocation memory arrays.
  • Object-oriented programming ( oop) in Matlab :
  • Creating classes, defining properties and methods,handling inheritance or event listener

App Building :

  • Designing graphical user interfaces, (GUI) interactively using App designer and callback programming.
  • Simulink & model-Based Design:
  • Introduction to block diagram, modeling, continuous/discrete dynamic system simulation and signal processing workflows