Master MATLAB through Guided Problem Solving

Master MATLAB through Guided Problem Solving, available at $89.99, has an average rating of 4.86, with 170 lectures, based on 4069 reviews, and has 24615 subscribers.

You will learn about 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 This course is ideal for individuals who are Anyone looking to build a career in engineering, physics, biology, finance, and many other fields by building Excellent MATLAB coding skills or Anyone wanting to progress beyond watching simple MATLAB tutorials to actually becoming an expert in MATLAB programming by solving real problems in scientific computing It is particularly useful for Anyone looking to build a career in engineering, physics, biology, finance, and many other fields by building Excellent MATLAB coding skills or Anyone wanting to progress beyond watching simple MATLAB tutorials to actually becoming an expert in MATLAB programming by solving real problems in scientific computing.

Enroll now: Master MATLAB through Guided Problem Solving

Summary

Title: Master MATLAB through Guided Problem Solving

Price: $89.99

Average Rating: 4.86

Number of Lectures: 170

Number of Published Lectures: 168

Number of Curriculum Items: 170

Number of Published Curriculum Objects: 168

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

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

Who Should Attend

Anyone looking to build a career in engineering, physics, biology, finance, and many other fields by building Excellent MATLAB coding skills

Anyone wanting to progress beyond watching simple MATLAB tutorials to actually becoming an expert in MATLAB programming by solving real problems in scientific computing

Target Audiences

Anyone looking to build a career in engineering, physics, biology, finance, and many other fields by building Excellent MATLAB coding skills

Anyone wanting to progress beyond watching simple MATLAB tutorials to actually becoming an expert in MATLAB programming by solving real problems in scientific computing

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!

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: (Important) How to Learn from this Course

Lecture 2: Stages of Learning Programming and Completing Projects

Lecture 3: pdf with complete lecture list and keywords

Lecture 4: Using the Q&A forum

Lecture 5: ALL MATLAB materials for the entire course in one zip file

Chapter 2: Getting Started

Lecture 1: Create, edit, and open scripts

Lecture 2: Write Comments in Lines and Blocks

Lecture 3: Using MATLAB for a Personal Budget

Lecture 4: Personalize MATLAB Colors

Lecture 5: Start MATLAB with an Encouraging Note

Chapter 3: Vectors and Variables

Lecture 1: Create Vectors and Matrices

Lecture 2: Unsolved: Valid and Invalid Matrices

Lecture 3: Working with Text (Characters and Strings)

Lecture 4: HTML Table from MATLAB Code

Lecture 5: Round pi to N significant Digits

Lecture 6: File/folder Information Using Structures

Chapter 4: Command Statements

Lecture 1: Create a Hilbert Matrix Using for-loops.

Lecture 2: Unsolved: Compare two while Loops

Lecture 3: Create an Upper-Triangular Matrix

Lecture 4: Random Count-Down Timer (Poisson-like)

Lecture 5: Display the day of 1 January

Chapter 5: Import and Export Data

Lecture 1: Save and Load Multiple Files

Lecture 2: Import Formatted Text Data

Lecture 3: Import Excel-format Data

Lecture 4: Convert US$ to Euros Using up-to-date Info

Chapter 6: Translate Formulas into Code

Lecture 1: Trig Functions and Gaussians

Lecture 2: Laplace and log-normal Distributions

Lecture 3: Complex Numbers and Eulers Formula

Lecture 4: Piecewise Functions

Lecture 5: Piecewise Function in one line of Code

Lecture 6: Sigmoid Function

Lecture 7: Unsolved: Sigmoid and Error Function

Lecture 8: Circular p-value and its Approximation

Chapter 7: Descriptive Statistics

Lecture 1: Compute Measures of Central Tendency

Lecture 2: Compute Variance and Standard Deviation

Lecture 3: Unsolved: Sort Data up and down

Lecture 4: Data Transformations (log, sqrt, rank)

Chapter 8: 2D Plotting

Lecture 1: Lines

Lecture 2: Bars and errorbars

Lecture 3: Dots

Lecture 4: Multidimensional Data with Colored Scatter

Lecture 5: Unsolved: imagesc vs. pcolor

Lecture 6: Histograms

Lecture 7: Uncertainty in Future Money (using patch)

Lecture 8: Blend Pictures Using Transparency

Lecture 9: Vertically Stacking Data Series

Lecture 10: Distance Matrix from Generated Points

Lecture 11: Gabor Patch Marginal Histograms

Lecture 12: List of other image-processing videos in this course

Chapter 9: 3D Plotting

Lecture 1: Sphere in a Cube

Lecture 2: Colorful Cube (a.k.a. the happy Borg ship)

Lecture 3: Expanding Wavelets with Surfaces

Lecture 4: Textured Gaussian Surfaces

Lecture 5: A Ball in 3D Color Space

Lecture 6: Plane in R3 Spanned by Two Vectors

Lecture 7: Complex Sinc Surface

Lecture 8: The Prickly Gabor Patch

Chapter 10: Segmentation

Lecture 1: Threshold-based Time Series Segmentation

Lecture 2: Derivative-based Time Series Segmentation

Lecture 3: Intensity-based Image Segmentation

Lecture 4: Identify Neurons in a Mouse Brain Slice

Chapter 11: Data Animations

Lecture 1: Random Floating Ball

Lecture 2: The Square Chases the Mouse

Lecture 3: The Magically Materializing Peaks

Lecture 4: Smooth Sailing: The Movie

Lecture 5: Real-time Audio Spectrum from Mic

Lecture 6: M?bius Transformation

Lecture 7: UFO on a Sandcastle

Chapter 12: Graphical User Interfaces

Lecture 1: Dialog Box for User Input

Lecture 2: Interface to Select a File

Lecture 3: Input and Message Boxes

Lecture 4: GUI to Create Random Landscapes

Lecture 5: GUIDE to Sigmoid Parameter Space

Chapter 13: Functions and Anonymous Functions

Lecture 1: Same-length Differentiation

Lecture 2: Damped Oscillator

Lecture 3: Unsolved: Damped Arcsine

Lecture 4: Find and Extract a Function Core

Lecture 5: Smooth Plotting Function with Options

Lecture 6: Unsolved: Zscore Function

Chapter 14: Find, Min, Max

Lecture 1: Find Point Closest to Specified Value

Lecture 2: Unsolved: Manual Peak-Picking

Lecture 3: Find Negative Extrema in a 2D Function

Lecture 4: Unsolved: Find Ridges of a 2D Surface

Lecture 5: Find Local Maxima

Lecture 6: Replace Image Pixels in an Intensity Range

Lecture 7: Find Signal Clipping Points

Instructors

Tim Buchalkas Learn Programming Academy
Professional Programmers and Teachers – 2M students

Mike X Cohen
Educator and writer

Rating Distribution

1 stars: 38 votes

2 stars: 30 votes

3 stars: 267 votes

4 stars: 1333 votes

5 stars: 2401 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!