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Tim Buchalka's Learn Programming Academy and Mike X Cohen

MATLAB is the premier programming language of scientific computing in university, research, and industry. Excellent MATLAB programming skills can make or break a career in engineering, physics, biology, finance, and many other fields.But how do you learn how to program in MATLAB? Sure, you can watch some tutorial videos online, but those videos generally focus on the most basic coding skills, like what is a variable and how to write a for-loop. Those are important foundations, but they won't make you competitive.If you want to be competitive, you need to become a master at MATLAB programming. And that's what you'll learn in this course.

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MATLAB is the premier programming language of scientific computing in university, research, and industry. Excellent MATLAB programming skills can make or break a career in engineering, physics, biology, finance, and many other fields.But how do you learn how to program in MATLAB? Sure, you can watch some tutorial videos online, but those videos generally focus on the most basic coding skills, like what is a variable and how to write a for-loop. Those are important foundations, but they won't make you competitive.If you want to be competitive, you need to become a master at MATLAB programming. And that's what you'll learn in this course.

This course is different from other MATLAB programming courses. Rather than having short videos that presents a simple piece of MATLAB syntax, this course starts from the real-world perspective: Problems in data science that you can solve with MATLAB.Do you need to learn how to filter your signal in MATLAB?  There's a section for that. Do you have a complicated formula and you need to translate it into MATLAB code and make a graph that simulates the formula with different parameters? Yeah, there's a section on that as well. Do you need to make a movie of a 3D simulation changing in color over time and then export as an .avi file? This course covers that as well.    

Maybe you want to learn how to make textured landscapes using fractal math, or use SVD to compute the low-rank approximation of a data matrix, or use nonlinear search methods to fit a 3-parameter Gaussian model to data? You guessed it it's all covered in this course.

If you are looking for a slow, gentle course that will take baby-steps to teach you what you could have learned on your own, then this is not that course.If you want to gain confidence in solving real-world problems in MATLAB coding to advance your studies, your research, and your career by learning MATLAB programming from a single course with >35 hours of hands-on instruction from a world-class scientist, teacher, and writer, then this course is definitely right for you.

Key topics covered.

The basic stuff: loops, functions, IO, etc. Core skills you need to be able to progress with MATLAB for scientific computing or data science. The more intermediate and advanced topics in the course include:

2D and 3D plotting, and data animations (movies)

Image and time series segmentation

Calculus and differential equations

Univariate and multivariate time series cleaning and analysis

Spectral (Fourier) and time-frequency analyses

Linear algebra including eigendecomposition, orthogonalization, and principal components analysis

Generating fractal pictures and time series

Nonparametric statistics and nonlinear model fitting

Get started today.

There is no doubt that MATLAB is the premier programming language of scientific computing and data science in university, research, and industry. 

The sooner you sign up for this course, the sooner you will be able to advance your career in engineering, physics, biology, finance (or other fields using MATLAB).

Why not get started today?

Click the Signup button to sign up for the course.

Enroll now

What's inside

Learning objectives

  • Intermediate to advanced matlab programming proficiency. this is *the only course* that develops intermediate and advanced programming skills.
  • Experience with real-world applications including signal processing, matrix decompositions, spectral analysis, linear and nonlinear model-fitting, and statistic
  • Gain skills to solve challenging problems in matlab, as opposed to memorizing syntax rules.
  • Data science projects and problem-solving in matlab

Syllabus

Course Introduction

How to get the most out of this course

How to become a master programmer

pdf with complete lecture list and keywords
Read more
Using the Q&A forum

All the code and external files from this course.

Getting Started

Learn about MATLAB scripts.

Learn several ways to comment your code.

Compute average daily budget based on monthly income/expenses.

Make your MATLAB experience colorful.

Specify start-up preferences.

Vectors and Variables

Create column and row vectors, and matrices.

Determine whether code is valid

Parse and modify text.

Use MATLAB to write dynamic html code.

Compute and print pi to any number of digits.

Use dir and structures to query file/folder information

Command Statements

Use for-loops to create special matrices based on a mathematical formula.

Determine the differences between two loops

Use for-loops and if statements to create a triangular matrix.

Implement a random Poisson-like count-down timer.

Compute the day of 1 January, any year

Import and Export Data

Use loops to export and import data without overwriting

Use fgetl to import data from a formatted text file.

Import data from an Excel file and identify missing data values.

Import data from the web to convert currencies.

Translate Formulas into Code

Compute and plot basic trig functions, and the Gaussian

Convert distribution functions into MATLAB.

Make complex numbers, apply Euler's formula, and test the law of exponents.

Implement a piecewise formula

Produce a piecewise function using one line of code.

Implement a 3-parameter sigmoid function

Parameterize the sigmoid to look like the ERF function

Implement a long and tedious function, and then its approximation.

Descriptive Statistics

Implement algorithms to compute the mean, median, and mode

Implement algorithms to compute variance and standard deviation

Sort numeric data

Transform datasets to have different distributions

2D Plotting

Random lines; curve from straight lines.

Generate data to learn about bar and errorbar.

Make scatterplots to show data.

Use color for multidimensional data on a 2D plot.

Determine the difference between two image plotting functions

Make histograms of log-normal distributions.

Use patches to visualize the future value of your money.

Use transparency to combine pictures.

View multichannel data in a single line plot.

Compute a distance matrix from mouse-generated points.

Create a Gabor patch and show its marginal distributions

A list of other videos in this course that cover image processing.

3D Plotting

Draw the 12 edges of a box, and put a sphere in the middle

Generate a cube of connected nodes.

Surface map of wavelets

Curved surface with various textures.

Define and plot a sphere in RGB space

Plot a plane defined by two 3D vectors.

Create a modern-art table using the sinc function

Create a Gabor patch and show with its normals

Segmentation

Draw patches to indicate extreme positive and negative time windows.

Identify jumps in a simulated stock market.

Segment a smoothed random image based on relative intensity.

Segment a high-res image to identify brain cells.

Data Animations

A ball randomly moves around in the figure.

A square moves to the mouse-click location.

Animate the famous "peaks" function to materialize slowly and randomly.

Generate a movie of traveling waves on standing waves.

Collect mic data and analyze in real time.

Watch how the Mobius transformation glides across the screen.

Create and animate a glowing ball on a surface

Graphical User Interfaces

Simple UI to input parameters and save picture.

Dialog box to select files and folders.

Simple GUIs to evalute chocolate consumption.

User interface to make adjustable 3D landscapes.

Create a GUI that helps understand the sigmoid parameters

Functions and Anonymous Functions

Write a function that returns the derivative while preserving length

Create an anonymous function to produce a damped oscillator

Implement a damped arcsine anonymous function and explore its parameter space

Inspect the median function to find the important code, and put that in a separate function.

Apply a mean smoothing filter and optionally plot the results.

write a function that computes the zscore with various options

Find, Min, Max

Find specific or best-match values in vectors and matrices.

Use datacursor to find a local minimum

Finding extreme points is not as easy as you might think!

Plot points on the ridges of a 2D landscape

Indentify local maxima of a sinc function

Change the color of mid-range intensity pixels

Mark time points where a signal gets clipped (e.g., amp saturation)

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Focuses on real-world data science problems, which allows learners to apply MATLAB skills in practical scenarios and advance their studies and careers
Covers intermediate and advanced topics like 2D/3D plotting, image segmentation, spectral analysis, and linear algebra, which are essential for complex data analysis
Includes hands-on instruction and code examples, which allows learners to actively engage with the material and develop practical MATLAB programming skills
Teaches skills to solve challenging problems in MATLAB, which helps learners move beyond memorizing syntax and develop problem-solving abilities
Requires a solid foundation in basic MATLAB programming, which means that learners without prior experience may need to acquire foundational knowledge first
Emphasizes problem-solving over gentle, step-by-step instruction, which may not be suitable for learners who prefer a slower-paced and more introductory approach

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Reviews summary

Matlab practical problem solving

According to learners, this course offers a practical problem-solving approach to mastering MATLAB. It delves into a wide range of intermediate and advanced topics crucial for scientific computing and data science, making it highly relevant for career and research. However, it is a challenging and fast-paced course that is not suitable for true beginners and requires a significant time commitment. Students looking to solidify their MATLAB skills through hands-on application in complex areas may find it valuable.
Covers a wide range of advanced topics.
"The syllabus covers an impressive number of advanced areas like signal processing and linear algebra."
"Provides good depth on specific advanced topics useful for research."
"Material is highly relevant for those working in technical fields using MATLAB."
Emphasizes real-world problem solving.
"Appreciated the strong focus on real-world problems rather than just syntax."
"Learning by doing practical problems was highly effective."
"The guided problem approach helped solidify understanding and build skills."
Demanding course, requires time.
"The course is quite demanding and requires a significant time investment."
"Needed substantial time outside lectures to grasp concepts and complete problems."
"Not a quick introductory course, requires dedication."
Challenging, best for intermediates.
"This course is definitely not for beginners; a solid foundation is needed."
"Required significant prerequisites and prior programming exposure."
"The pace is quite fast and covers complex topics quickly."

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 Master MATLAB through Guided Problem Solving with these activities:
Review Linear Algebra Fundamentals
Solidify your understanding of linear algebra concepts, which are crucial for understanding matrix decompositions and PCA covered in the course.
Show steps
  • Review key concepts like vectors, matrices, and linear transformations.
  • Practice solving linear equation systems.
  • Work through examples of eigenvalue and eigenvector calculations.
Read 'MATLAB for Dummies'
Familiarize yourself with the basics of MATLAB syntax and environment before diving into more complex problem-solving.
View MATLAB For Dummies on Amazon
Show steps
  • Skim through the chapters on basic syntax and data types.
  • Try out the example code snippets in MATLAB.
  • Focus on chapters related to plotting and data visualization.
Implement Basic Statistical Functions
Reinforce your understanding of descriptive statistics by implementing functions like mean, median, and standard deviation in MATLAB.
Show steps
  • Write MATLAB functions to calculate mean, median, and standard deviation.
  • Test your functions with various datasets.
  • Compare your results with MATLAB's built-in functions.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Document Code with Comments
Improve code readability and understanding by consistently documenting your MATLAB code with clear and concise comments.
Show steps
  • Add comments to explain the purpose of each code section.
  • Use comments to describe the inputs and outputs of functions.
  • Explain complex calculations or algorithms with comments.
Analyze Stock Market Data
Apply your MATLAB skills to analyze real-world stock market data, including time series analysis and segmentation.
Show steps
  • Download historical stock market data from a reliable source.
  • Implement time series analysis techniques to identify trends.
  • Use segmentation methods to identify jumps in the stock market.
  • Visualize your findings using MATLAB plots and charts.
Read 'Mastering MATLAB'
Deepen your understanding of advanced MATLAB concepts and techniques for solving complex problems.
View Mastering MATLAB on Amazon
Show steps
  • Focus on chapters related to advanced plotting and data visualization.
  • Study the examples of solving differential equations in MATLAB.
  • Explore the chapters on signal processing and image analysis.
Contribute to a MATLAB Library
Enhance your MATLAB skills by contributing to an open-source MATLAB library, gaining experience in collaborative coding and software development.
Show steps
  • Find an open-source MATLAB library that aligns with your interests.
  • Identify a bug or feature that you can contribute to.
  • Submit your code and documentation to the library maintainers.
  • Respond to feedback and revise your code as needed.

Career center

Learners who complete Master MATLAB through Guided Problem Solving will develop knowledge and skills that may be useful to these careers:
Signal Processing Engineer
A signal processing engineer designs, develops, and tests algorithms and systems for processing signals, such as audio, image, or sensor data. This course directly aligns with the needs of a signal processing engineer, as evidenced by the inclusion of signal filtering, spectral analysis, and time-frequency analyses. The course's hands-on approach to solving signal processing problems in MATLAB, combined with its coverage of image and time series segmentation, makes it a very valuable resource.
Research Scientist
A research scientist designs and conducts experiments, analyzes data, and publishes findings to advance knowledge in a specific field. This course helps build a foundation for success as a research scientist because many scientific and engineering disciplines use MATLAB for data analysis, modeling, and simulation. The course's emphasis on problem solving in MATLAB is very relevant here. Specifically, the skills in calculus, differential equations, spectral analysis, and image processing covered in the course will be valuable for research projects.
Image Processing Specialist
An image processing specialist works with algorithms and software to manipulate, enhance, and analyze digital images. This course covers image processing and segmentation, which are essential for analyzing images. Using MATLAB, the premier programming language, the user will gain the technical foundations needed to succeed as an image processing specialist. Skills developed in this course may be useful for enhancing images, removing noise, identifying objects, and extracting valuable information from visual data.
Quantitative Researcher
A quantitative researcher applies mathematical and statistical techniques to conduct research and develop new models or algorithms often requiring an advanced degree. This course is useful because MATLAB is often used in quantitative research, particularly in fields like finance and engineering. The course's focus on solving real-world problems in MATLAB, including statistical analysis, linear algebra, and nonlinear model fitting, helps develop a strong analytical ability.
Data Scientist
A data scientist analyzes complex data sets to extract meaningful insights and develop data-driven solutions. This course may prove helpful because MATLAB is a premier programming language for data science. Proficiency in MATLAB, as emphasized in the course, positions one well to tackle real-world data challenges. The course's focus on data science problems, signal filtering, statistical analysis, and model fitting directly translates to the core responsibilities of a data scientist. Exposure to time series analysis and machine learning techniques covered in the course can enhance a data scientist's analytical toolkit.
Computational Biologist
A computational biologist applies computational techniques to analyze biological data, model biological systems, and gain insights into complex biological processes often requiring an advanced degree. This course may equip you with the necessary skills, because MATLAB is a common tool in computational biology. Translating formulas into MATLAB code is important for making a graph that simulates the formula with different parameters. This course would allow a computational biologist to fit a three-parameter Gaussian model to data.
Quantitative Analyst
A quantitative analyst, often working within the finance industry, uses mathematical and statistical methods to analyze financial data, assess risk, and develop trading strategies. This course may be useful because MATLAB is a widely-used tool in quantitative finance. With this course's focus on translating formulas into code, simulating with varying parameters, and applying time series analysis, you can enhance your skillset as a quantitative analyst. The course's coverage of statistical analysis, linear algebra, and nonlinear model fitting provides a strong foundation for quantitative analysis.
Biostatistician
A biostatistician applies statistical methods to analyze data related to health and biology often requiring an advanced degree. This course may prove useful because MATLAB is a tool for statistical computing and data visualization in biostatistics. The course's emphasis on statistical analysis, model fitting, and time series analysis directly supports the work a biostatistician does. Through this course, a biostatistician can get better at working with data.
Machine Learning Engineer
A machine learning engineer develops and implements machine learning models and algorithms to solve real-world problems often requiring an advanced degree. This course may prove helpful because MATLAB is a useful tool for prototyping and deploying machine learning algorithms. The course's coverage of linear algebra, statistical analysis, and model fitting provides a strong foundation for machine learning. A machine learning engineer may gain knowledge that helps one to create practical models using MATLAB.
Econometrician
An econometrician uses statistical methods to analyze economic data and test economic theories often requiring an advanced degree. This course may prove helpful because MATLAB is used in econometrics for time series analysis, regression modeling, and simulation. The course's coverage of time series cleaning, analysis, and spectral analysis are particularly relevant. An econometrician will be able to learn MATLAB, a premier programming language.
Data Analyst
A data analyst collects, cleans, and analyzes data to identify trends, patterns, and insights that can inform business decisions. This course may prove helpful because MATLAB is a powerful tool for data analysis and visualization. The skills acquired in this course through real-world problem solving will allow a data analyst to thrive. Knowledge of descriptive statistics and linear algebra can help one to succeed in data analysis.
Financial Modeler
A financial modeler creates and uses mathematical models to analyze financial data, forecast performance, and support decision-making. This course may prove helpful because MATLAB is often used in finance for modeling and simulation. The financial modeler benefits from translating formulas into MATLAB code and making graphs that simulate the formulas, as covered in this course. The skills you learn in this course are useful for building complex financial models and performing simulations.
Robotics Engineer
A robotics engineer designs, develops, and tests robots and robotic systems for various applications. This course may be useful because MATLAB is often used for the design, simulation, and control of robots. The course's coverage of linear algebra, calculus/differential equations, and data animations makes it particularly relevant. A robotics engineer will have use for these skills when controlling various robotic designs.
Systems Engineer
A systems engineer designs, integrates, and manages complex systems, ensuring that all components work together effectively. This course may be quite useful because MATLAB is often used for system modeling, simulation, and analysis. The course's coverage of calculus, differential equations, and linear algebra provides a systems engineer with the analytical tools to succeed. A systems engineer benefits from real-world problem solving in MATLAB.
Test Engineer
A test engineer designs and implements tests to ensure the quality and reliability of products and systems. This course may be helpful because MATLAB is often used for test automation, data analysis, and signal processing in testing environments. The course's coverage of signal filtering, spectral analysis, and image processing enables one to design automated tests. Use the course to help advance your career in test engineering.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Master MATLAB through Guided Problem Solving.
Comprehensive guide to MATLAB programming, covering a wide range of topics from basic syntax to advanced techniques. It's particularly useful for students who want to deepen their understanding of MATLAB and become proficient in solving complex problems. This book is commonly used as a textbook at academic institutions. It adds more depth to the existing course.
Provides a gentle introduction to MATLAB, covering basic syntax and functionalities. It's particularly helpful for students with little to no prior programming experience. While not a deep dive into advanced topics, it can serve as a useful reference for foundational concepts. It is most valuable as additional reading to build confidence.

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