Course Overview & Running Example

What this MATLAB course covers, how to use it, prerequisites, and the running example used throughout.

Track: Computer Science → Programming Languages → MATLAB

Category: Data Science / Scientific Computing Levels: Beginner → Intermediate → Advanced → Expert

Audience: Engineering students, scientists, control/signal/automotive engineers, data analysts and interview candidates

Course Overview

MATLAB ("MATrix LABoratory") is a high-level language and interactive environment by MathWorks for numerical computing. Everything in MATLAB is an array, so mathematics written on paper — vectors, matrices, equations — translates almost directly into code. It is used for:

Engineering calculations and simulation (mechanical, electrical, civil, aerospace) Signal and image processing

Control system design (with Simulink for model-based design)

Automotive development: calibration, data analysis, model-based design and automatic code generation for ECUs

Data analysis, statistics and machine learning Rapid prototyping of algorithms before implementing them in C/C++

This course starts from your very first command and ends with numerical methods, ODE simulation, signal processing, control loops, object-oriented programming, performance tuning and engineering applications.

How This Course Is Organized The course has 4 stages and 37 modules. Every module follows the same structure:

The explanation, split into sub-topics Why It Matters Where the topic shows up in real engineering work The general form of the feature Runnable MATLAB scripts The real output of the scripts Pitfalls to avoid How professionals use the feature What interviewers ask about it Exercises to try yourself

Multiple-choice, true/false, predict-the-output and find-the-bug questions with answers A small problem with a worked solution A Note on Verified Output

MATLAB is commercial software. Every example in this course was written in standard MATLAB syntax and actually run with GNU Octave 11.3, the free interpreter that executes MATLAB code; the outputs shown are exactly what it printed. To keep the code portable, the examples:

use % comments, ~=, single-quoted character vectors, and disp/fprintf for output;

put helper functions in their own .m files (they are shown with the examples);

use only core MATLAB functions (no toolbox needed).

Two differences you may notice when you run the same code in MATLAB:

Automatic display format. When a statement has no semicolon, MATLAB prints x = on one line, a blank line and the value indented, while Octave prints x = 5 compactly. The values are identical; fprintf and disp output is the same in both.

Toolbox-only and MATLAB-only features (string arrays "...", table, timetable, tf/step from the Control System Toolbox, Simulink) are explained with code clearly marked *MATLAB only — not run in this course*.

Random numbers (rand, randn) and timings differ between MATLAB and Octave and between machines.

Learning Objectives

By the end of this course you will be able to:

Use the MATLAB desktop, Command Window, scripts and the documentation effectively.

Work with MATLAB's data types: numeric classes, logical, char, cell arrays, structures and maps.

Create, index, reshape and combine vectors and matrices, and use logical indexing.

Write clear control flow, functions, anonymous functions and function handles.

Replace loops with vectorized code and preallocate when loops are needed.

Read and write text, CSV and MAT files.

Create and customize 2-D and 3-D plots.

Handle errors robustly and debug MATLAB code.

Solve engineering problems numerically: linear systems, polynomials, interpolation, curve fitting, integration, ODEs and optimization.

Analyse signals with the FFT and digital filters, and simulate control loops.

Build object-oriented MATLAB programs with classdef.

Apply MATLAB to engineering and automotive tasks, and answer MATLAB interview questions.

Prerequisites

Basic computer literacy; no prior programming experience is required.

High-school algebra; familiarity with vectors and matrices helps in later modules (they are explained as they appear).

MATLAB (any recent release, R2016b or newer) or the free GNU Octave (8 or newer).

The Course Running Example

Many examples use the same small engineering scenario so the code reads like real work:

Vehicle test bench Measures battery voltage, temperature and current

Electronic control units such as VCU, BMS, GW with firmware versions

Voltage ripple, engine speed decoded from CAN bytes, sensor readings with noise

Calibrate sensors, filter noise, fit models, simulate a motor speed controller

flowchart LR
    DATA["Measurements: CSV, CAN log, sensors"] --> LOAD["Load and clean (Modules 13-17)"]
    LOAD --> ANALYZE["Analyse: statistics, fitting, FFT (Modules 21-27)"]
    ANALYZE --> MODEL["Model and simulate: ODEs, control (Modules 23, 26)"]
    MODEL --> REPORT["Plot and report (Modules 18-19)"]