Data Visualization with MATLAB - Projects and Examples from Udemy

Why Visualize Data?

Since 80 percent of the sensory information the brain receives comes from our eyes, the visual presentation of data is the natural choice.

It helps you to identify and emphasize areas of interest in data behavior, to express your thoughts, observations, and conclusions to others in a quick and intuitive way.

Why MATLAB?

1. Ease of Use

Programs may be easily written and modified with the built-in integrated development environment and debugger.

2. Platform Independence

The language is supported on Windows, Linux, Unix, Macintosh. Programs written on any platform will run on all of the other platforms.

4. Device-Independent Plotting

The plots and images can be displayed on any graphical output device supported by the computer on which MATLAB is running. This capability makes MATLAB an outstanding tool for visualizing data.

5. Full set capabilities

It includes features for representation of two-dimensional and three-dimensional diagrams, three-dimensional volume visualization, animation, tools to create diagrams interactively and the possibility of exporting to the most popular graphic formats. It is possible to customize diagrams adding multi-axes, change the colors of the lines and markers, add annotations, LaTeX expressions, legends and other plotting options.

Why this course?

Breaks the complex plot techniques down into simplistic steps.
Easy and intuitive approach from professional trainers.
Ideal for students, academics, scientists.
Suitable for beginner programmers.

What's inside

Learning objectives

Create 2d plots with matlab
Create 3d plots with matlab
Create volumetric plots with matlab

Express yourself by matlab plots
Export figures from matlab for use in documents
Have basic understanding of quality code in matlab

Create 2d plots with matlab
Create 3d plots with matlab
Create volumetric plots with matlab
Express yourself by matlab plots
Export figures from matlab for use in documents
Have basic understanding of quality code in matlab

Syllabus

Introduction

Basic Settings and Basic Plot

Basic Settings - Part 2

2D Plots and Basic Properties

Customizing Plots Part 1 - Labels, Grid, Font Styling

Customizing Plots Part 2 - Titles

Customizing Plots Part 3 - Axis Limits

Customizing Plots Part 4 - Line width and color

Customizing Plots - Source code

Hold on! Multiple Plots on a Single Figure?

Hold on - Source code

Legend - What does this line do?

Legend - Source code

Multiple Plots Part 1 - Figures

Figures - Source code

Multiple Plots Part 2 - Subplot

Subplot - Source code

Customizing Plots (Advanced) Part 1 - Markers

Markers - Source code

Customizing Plots (Advanced) Part 2 - Ticks and Grid Manipulation

Ticks and Grid Manipulation - Source code

Customizing Plots (Advanced) Part 3 - Ticklabel and Lineplots

Ticklabel and Lineplots - Source code

Two Y Axes on a single figure? Call PlotYY! (2D Project)

PlotYY 2D Project - Source code

3D Plots, Quality Code and Animation

Plot3 - Line plots in 3 dimensions

Plot3 - Source code

Meshgrid - Doorway to 3D+ plots

Meshgrid - Source code

Contour Plot - Wanna plot a mountain?

Contour Plot - Source code

3D Project

3D Project Quality Code

3D Project and Quality Code - Source code

4D & 5D Plots

Slice and Dice Part 1 - 4D Slice Plots

Slice and Dice P1 - Source code

Slice and Dice Part 2 - Moving Slices

Slice and Dice P2 - Source code

Slice and Dice Part 3 - 5D Slice Plots

Slice and Dice P3 - Source code

4D, 5D and Animated Scatter Plots

Scatter3 - Source code

Exporting

Export your figure and use it anywhere!

Exporting - Source code

Hierarchy of MATLAB Graphical Objects and 2D Template

The Hierarchy of Graphical Objects in MATLAB

Saving and Loading Your Variables

SPECIAL GIFT: Predefined 2D Template To Visualize Your Data Easier and Faster

2D Template Source Code

Designing Interactive Plots

Making Your Plots Interactive - Callbacks - What is a Callback?

Callbacks Example - Change Axes Properties By Pressing a Key

SPECIAL GIFT: 3D Explorer - For Easier Visual Exploration of 3D MATLAB Plots

3D Explorer - Source Code

Visualizing up to 3D Matrices in a Plot

Introduction to the Project

Visualizing an image(array data) within a plot as cells

Fixing the stylings of the plot and the colorbar

Making the data cursor show custom (relevant) information

Matrix Visualization - Source Code

Bonus Section

Further Reading

Line styles, Marker types and Colors

Colormaps

Bonus Lecture: Get my other courses with a Huge Discount!

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 Data Visualization with MATLAB - Projects and Examples with these activities:

Review Basic Plotting Concepts

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Reinforce fundamental plotting concepts in MATLAB to ensure a solid foundation for more advanced visualization techniques covered in the course.

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Review the documentation for the `plot` function.
Practice creating simple line plots with different line styles and colors.
Experiment with adding titles, labels, and legends to your plots.

Read 'MATLAB Graphics' by Michael McPartlin

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Deepen your understanding of MATLAB graphics capabilities and explore advanced techniques for creating compelling visualizations.

View Putting Knowledge to Work on Amazon

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Read the chapters relevant to 2D and 3D plotting.
Experiment with the examples provided in the book.
Try to apply the techniques learned to your own data visualization projects.

Recreate Example Plots

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Solidify your understanding of different plot types and customization options by recreating example plots from the course materials or MATLAB documentation.

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Choose a plot example from the course or MATLAB documentation.
Write the MATLAB code to recreate the plot from scratch.
Compare your plot to the original and identify any discrepancies.
Adjust your code until your plot matches the original.

Three other activities

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Show all six activities

Visualize Real-World Data

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Apply your MATLAB visualization skills to a real-world dataset to gain practical experience and create meaningful insights.

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Find a publicly available dataset that interests you.
Import the data into MATLAB.
Explore the data and identify interesting patterns or trends.
Create visualizations that effectively communicate your findings.
Document your project and share your visualizations with others.

Create a Visualization Portfolio

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Showcase your MATLAB visualization skills by creating a portfolio of your best plots and projects.

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Select your best visualizations from the course and your own projects.
Write a brief description for each visualization, explaining the data and the insights it reveals.
Organize your visualizations into a portfolio using a website or presentation software.
Share your portfolio with potential employers or collaborators.

Contribute to a MATLAB Visualization Project

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Enhance your skills and contribute to the MATLAB community by participating in an open-source visualization project.

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Find an open-source MATLAB visualization project on platforms like GitHub.
Review the project's documentation and code.
Identify areas where you can contribute, such as bug fixes, new features, or improved documentation.
Submit your contributions to the project maintainers.

Career center

Learners who complete Data Visualization with MATLAB - Projects and Examples will develop knowledge and skills that may be useful to these careers:

Epidemiologist

An epidemiologist studies the patterns, causes, and effects of health and disease conditions in defined populations. This course helps an epidemiologist given the high importance of data visualization within the field. The course teaches how to create two dimensional and three dimensional plots with MATLAB, express data by MATLAB plots, and export figures from MATLAB for use in documents. An epidemiologist needs to be able to visualize and show data clearly, and this helps do so.

See salaries and explore the career path for Epidemiologist

Image Processing Engineer

An image processing engineer develops algorithms and systems for processing and analyzing images. Visualizing image data is essential for tasks such as image enhancement, segmentation, and object recognition. This course helps an image processing engineer by teaching them how to display, manipulate, and analyze image data in MATLAB. Learning to create two dimensional and three dimensional plots, customize plots, and visualize matrices helps an image processing engineer develop and validate their algorithms. The interactive plot designs can be especially helpful.

See salaries and explore the career path for Image Processing Engineer

Biomedical Engineer

A biomedical engineer applies engineering principles to solve problems in medicine and biology. They often work with complex data from medical imaging, physiological monitoring, and genomics. Data visualization is essential for understanding these data and communicating findings to healthcare professionals. This course helps a biomedical engineer by providing the skills to create compelling visualizations using MATLAB. The ability to create two dimensional, three dimensional, and volumetric plots within MATLAB may be useful, as is the knowledge of plot customization with labels, titles, and annotations.

See salaries and explore the career path for Biomedical Engineer

Statistician

A statistician collects, analyzes, and interprets numerical data. This course may be useful to a statistician as it teaches them about visualizing data using plots. The course teaches how to create two dimensional and three dimensional plots with MATLAB, as well as how to hold multiple plots on a single figure. These skills may be beneficial for a statistician who wants to visualize data, trends, and models, and to present these to others.

See salaries and explore the career path for Statistician

Research Scientist

A research scientist designs and conducts experiments, analyzes data, and disseminates findings through publications and presentations. Since research often involves complex data, data visualization is essential for understanding patterns and trends, and for effectively communicating results. This course helps a research scientist by providing the skills to create compelling visualizations using MATLAB. The ability to create two dimensional, three dimensional, and volumetric plots within MATLAB may be useful, as is the ability to customize plots with labels, titles, and annotations.

See salaries and explore the career path for Research Scientist

Geospatial Analyst

A geospatial analyst uses geographic information systems to analyze spatial data and create maps. Visualizing geospatial data is crucial for identifying patterns, trends, and relationships. This course helps a geospatial analyst by providing the skills to create compelling visualizations using MATLAB. Learning to create two dimensional and three dimensional plots, customize plots, and export figures will help a geospatial analyst effectively analyze and present their spatial data. The sections on contour plots and slice plots could be particularly relevant.

See salaries and explore the career path for Geospatial Analyst

Data Scientist

A data scientist analyzes large datasets to extract meaningful insights and inform strategic decisions. This course may be useful for a data scientist because data visualization is a critical component of this role. Data scientists often use tools like MATLAB to create visualizations that communicate their findings to both technical and non-technical audiences. Learning how to create effective 2D, 3D, and volumetric plots, as well as how to customize and export those plots, helps a data scientist present complex data simply. The sections on customizing plots, exporting figures, and visualizing matrices addresses the needs of a data scientist.

See salaries and explore the career path for Data Scientist

Simulation Engineer

A simulation engineer develops and uses computer models to simulate physical systems and predict their behavior. They often need to visualize simulation results to understand system dynamics and identify potential problems. This course may be useful for a simulation engineer because it provides a comprehensive introduction to data visualization techniques in MATLAB, a popular simulation software. The ability to create three dimensional and volumetric plots, customize plots, and export figures will help a simulation engineer effectively analyze and present their simulation results. This is especially true when considering the sections on slice plots.

See salaries and explore the career path for Simulation Engineer

Data Analyst

A data analyst examines data in order to reach conclusions about that data. They may find this course useful as it teaches them about making plots of data with MATLAB, and exporting figures from MATLAB for use in presentations and analyses. This course may be useful to a data analyst who seeks to broaden their skillset and learn a new and useful technology. The course teaches customizing plots and subplots, which can be useful to a data analyst.

See salaries and explore the career path for Data Analyst

Mechanical Engineer

A mechanical engineer designs, develops, and tests mechanical devices and systems. They often use data visualization to analyze simulation results, experimental data, and manufacturing processes. This course may be useful because provides a comprehensive introduction to data visualization techniques in MATLAB. The ability to create two and three dimensional plots, customize plots, and create animations helps a mechanical engineer analyze and present their data effectively. One who wishes to be a mechanical engineer may benefit from the course's explanation of multiple y axes.

See salaries and explore the career path for Mechanical Engineer

Researcher

A researcher is someone who investigates new topics and develops new techniques. Research is a broad term, and researchers are common in scientific and engineering fields. Researchers in particular may find this course helpful as it relates to how to create two dimensional and three dimensional plots with MATLAB, express themselves in scientific publications, and have a basic understanding of quality code in MATLAB. As such, any researcher can consider this course.

See salaries and explore the career path for Researcher

Machine Learning Engineer

A machine learning engineer builds, tests, and deploys machine learning models. This course may be useful to a machine learning engineer who wants to visualize their data in new ways. The course teaches how to create two dimensional and three dimensional plots with MATLAB, which can be integrated into a machine learning workflow. Additionally, the course teaches the creation and interpretation of complex plots.

See salaries and explore the career path for Machine Learning Engineer

Acoustic Engineer

An acoustic engineer deals with the design, analysis, and control of sound and vibration. Visualizing acoustic data, such as frequency spectra and sound pressure levels, is crucial for understanding sound propagation and noise control. This course may be useful for an acoustic engineer as it provides hands-on experience with creating a variety of plots in MATLAB. Learning to customize plots and export figures helps an acoustic engineer effectively communicate their findings to architects and other engineers. The course focuses on multiple y axes, which can be useful for an acoustic engineer.

See salaries and explore the career path for Acoustic Engineer

Quantitative Analyst

A quantitative analyst develops and implements mathematical models for financial analysis and risk management. Visualizing financial data is crucial for identifying trends, patterns, and anomalies. This course may be useful for a quantitative analyst because it provides hands-on experience with creating a variety of plots in MATLAB, a commonly used tool in the finance industry. Learning to customize plots and export figures helps a quantitative analyst effectively communicate their findings to traders and portfolio managers. The course's sections on customizing plots with titles, labels, and annotations may be particularly relevant.

See salaries and explore the career path for Quantitative Analyst

Teacher

A teacher is an educator. They work to educate students of varying age groups and various skill levels. They may find this course helpful as they teach other students, especially those in STEM fields. The ability to export figures from MATLAB for use in documents and other teaching materials may be particularly helpful. This course teaches basic settings for MATLAB, which teachers can then impart to their students. An educator can benefit from the MATLAB skills in this course.

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Data Visualization with MATLAB - Projects and Examples

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