Matlab

Programming and Data Analysis with Matlab

Data Analysis4.9(73)6h 53m29 lectures6 sections

What you'll learn

  • Install Matlab and type commands
  • Perform basic operations on matrices
  • Solve linear equations
  • Use control flow
  • Build data and plot it
  • Process images and remove noise
  • Process audio signals
  • Use the Fourier transform and filters
  • Apply probability and hypothesis testing

About this course

This course teaches programming, data analysis and data visualization with Matlab, a language used by engineers and scientists for calculations and research. You start by learning what Matlab is, how to install it and how to type commands, then basic operations on matrices, functions, constants and solving linear equations, along with control flow such as If, else, While and For. Next you learn how to build data, plotting, subplots and three-dimensional graphics. Then you work on image processing, noise removal and edge detection, and on audio processing, the Fourier transform, and high-pass, low-pass, band-pass and band-stop filters. In the final part you learn probability, random values, density and distribution functions and hypothesis testing. The course suits engineering and science students and researchers, and no previous programming experience is required. Afterward you will be able to write Matlab programs, analyze and plot data and process images and audio. The teaching is in Arabic with practical examples on images, audio and data, so you understand the idea and try it yourself.

Expected outcomes

  • Master programming using MATLAB.
  • Handle and analyze data professionally.
  • Design advanced analytical graphs.
  • Apply MATLAB tools for data processing and analysis.

Learner reviews

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    Course content

    1

    Programming and Data Representation using Matlab

    6 lectures
    1. What is MATLAB and How to Install It?Introduces MATLAB, short for Matrix Laboratory, as a programming and numeric computing platform that treats every variable as a matrix, lists its uses, then explains downloading it and installing it from an ISO file.14:07
    2. Introduction to MATLAB and Command WritingIntroduces the MATLAB environment and its windows such as the current folder, command window and workspace, and explains typing commands, storing variables and text, saving and loading the workspace, with a sine plot example using linspace and plot.15:30
    3. Basic Operations on ArraysExplains basic matrix operations in MATLAB: addition, subtraction and multiplication with its conditions, accessing elements by index, operator precedence, element-wise operations, and the dot, outer and cross products of vectors.18:44
    4. Functions and ConstantsExplains functions and constants in MATLAB such as ans, pi, i, j, Inf and NaN, functions like sqrt, negative roots and the identity matrix eye, and how to write, save and call a custom function on a whole matrix.19:25
    5. Solving Linear Equations in MATLABExplains solving linear equations in MATLAB by representing them with matrices, computing the determinant and inverse to find the solution, eigenvalues and eigenvectors, and the norm function for measuring vector length.18:13
    6. Control Flow in MATLAB (If/else, While, For)Explains control flow structures in MATLAB: sequential, conditional and repetitive flow, if/else statements, for and while loops with practical examples, and parallel execution of tasks that can be split.18:44
    2

    Data Construction

    5 lectures
    1. Data StructuresExplains MATLAB data structures: matrix, vector and scalar, then struct, cell and table, how to define fields and nest structures inside each other, along with the whos and class commands.15:53
    2. Data PlottingExplains 2D plotting in MATLAB with plot, generating the range with linspace, formatting lines and markers, saving the figure as an image, and splitting a figure into several plots with tiledlayout.17:05
    3. Maps and Graphs Suitable for Data AnalysisExplains charts useful for data analysis in MATLAB: bar charts, histograms, pie charts with labels and an exploded slice, and comparing plot with scatter to display individual points.11:39
    4. Saving and Loading DataExplains importing and exporting data in MATLAB: reading and writing Excel files with xlsread and xlswrite, CSV files with csvread and csvwrite, and saving and loading the workspace in MAT files with save and load.8:31
    5. Subplots and 3D RepresentationExplains subplots with the subplot function as an easier alternative to tiledlayout, then 3D plotting using meshgrid, surf and contour to show the Z value for each X and Y point.7:41
    3

    Audio Processing and Analysis in Matlab

    8 lectures
    1. SoundExplains sound theoretically as a longitudinal wave and its conversion to a digital signal through sampling and quantization, then reading an audio file in MATLAB with audioread and playing it with sound.9:28
    2. Audio Signal ProcessingExplains audio signal processing in MATLAB: reading samples and the sampling rate, computing clip duration, swapping channels, reversing the sound, writing an audio file, and reducing samples with downsample and its effect on speed.9:18
    3. Fourier TransformExplains the Fourier transform as the idea that any signal is a sum of sinusoids with different frequencies and amplitudes, moving it from the time domain to the frequency domain, then applies it in MATLAB with FFT, separating real and imaginary parts.23:51
    4. Study of Fourier Transform for Sine WaveStudies the Fourier transform of a sine signal with FFT, then the short-time Fourier transform and the spectrogram to see how frequencies change over time for a signal whose frequency grows linearly, and the effect of window size.14:35
    5. High Pass Filter (HPF)Explains audio filters and the high pass filter that attenuates frequencies below the cutoff, building it in MATLAB with fir1, visualizing it with the Filter Visualization Tool, and the effect of changing the cutoff frequency on the signal.20:47
    6. Low Pass Filter (LPF)Explains the low pass filter that passes frequencies below the cutoff and attenuates higher ones, building it with fir1, applying it to an audio signal with filter, and comparing the signal before and after filtering.8:52
    7. Band Pass Filter (BPF)Explains the band pass filter that passes a range between two frequencies and attenuates the rest, building it with fir1 by setting the filter order and range, previewing it, applying it with filter and comparing the signal before and after.8:10
    8. Band Stop Filter (BSF)Explains the band stop filter that blocks a range between two frequencies and passes the rest, building it with fir1 using the stop option, applying it to a sound, and comparing the signal before and after and the effect of changing the stop band.9:27
    4

    Image Processing and Analysis in Matlab

    4 lectures
    1. ImagesExplains how MATLAB represents an image as three RGB color matrices per pixel, grayscale levels, and reading an image, showing it with imshow and saving it in different formats.15:37
    2. Some Operations on ImagesExplains basic image operations in MATLAB: reading with imread and showing with imshow, flipping an image vertically and horizontally, displaying several images with imtile, and separating and displaying the red, green and blue components individually.7:39
    3. The Gaussian Filter and Noise Removal from the Image (Image Blurring)Explains image filtering with a 2D filter based on convolution, building a Gaussian filter from the two-variable normal distribution to blur an image in MATLAB, and comparing the original and blurred images with imtile.21:43
    4. Removing Various Types of Noise and Edge Detection in the ImageExplains image noise types such as salt and pepper and speckle, filters to remove it including linear, mean, median and adaptive, comparing their results, then detecting image edges with the Sobel and Canny algorithms.21:00
    5

    Probabilities

    5 lectures
    1. Probabilities in MATLABIntroduces probability in MATLAB: computing how often a value occurs in a series of numbers, disjoint and independent events, drawing a histogram, and computing the probability of events such as a number being even.15:45
    2. Random Values Taken from Probability DistributionsExplains probability distributions and drawing random values from them in MATLAB with randi, rand and randn, plotting histograms, and simulating a biased coin toss with a custom function to estimate its distribution.11:07
    3. The Birthday ParadoxExplains the birthday paradox in probability: the chance that at least two people in a small group share a birthday, computing it in MATLAB through the complementary event and explaining why the result seems counterintuitive.19:50
    4. Probability Density Function and Cumulative Distribution Function PDF & CDFExplains the difference between continuous and discrete variables, the probability density function PDF and cumulative distribution function CDF, the normal distribution and the effect of standard deviation, and computing mean and variance in MATLAB.18:28
    5. Testing HypothesesExplains hypothesis testing to check whether data follows a normal distribution, with the null and alternative hypotheses and the p-value, applying tests such as Jarque-Bera, Kolmogorov-Smirnov and the two-sample test in MATLAB.11:59
    6

    Extensions

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    Instructor

    Dr. Eng. Mahmoud Ahmed

    Dr. Eng. Mahmoud Ahmed

    Software and network engineer with a PhD in data analysis and representation, and an international lecturer.
    2,591 views1 courses

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