Use this quick guide to learn what MATLAB is used for and how you can get started.
MATLAB is short for “matrix laboratory.” It is a high-level programming language and platform that works with matrices and arrays rather than individual numbers. Designed for scientists and engineers, MATLAB is often used in textbooks as an instructional tool for college-level mathematics, science, and engineering. It allows for the most direct and natural expression of matrix and array mathematics.
There are five components comprising MATLAB. These include:
MATLAB is an interpreted language that can be used to create applications of varying sizes and complexities. It’s also multi-paradigm, meaning you can use it for functional, imperative, procedural, or object-oriented programming. Notable features of the MATLAB language include data visualization, rapid numeric calculations and analyses, and built-in tools for editing and debugging software.
The MATLAB working environment is an interactive platform comprising various tools for statistical calculations and writing, running, and plotting code. The interface includes the following features: a command window for typing single or multiple lines; a script editor for accessing existing or creating new files; an address bar; a dedicated workspace window; and a folder tree.
MATLAB has a large library of computational algorithms. It contains elementary mathematical functions such as sin, cos, and tan, and more complex expressions such as matrix eigenvalues.
Handle Graphics is a MATLAB concept and methodology. Nearly all plotting functions will return a handle to the graphics object. Users can use these handles to access, view, and modify all the object’s properties.
MATLAB includes an API to support external programs and interfaces despite being a self-contained environment. Its supported functions include data importation and exportation (to and from the MATLAB environment), facilitation of client/server relationships with external programs, and calling Fortran or C programs from MATLAB.
The MATLAB programming platform is used to design, develop, and analyze systems and products. Originally, it was created for accessing software developed by the LINPACK and EISPACK projects. The MATLAB we know today has numerous use cases thanks to many contributions from users over the years. Examples include:
Large-scale computations
Algorithm development
Application development
Embedded system development
Control systems engineering
Deployment of Internet of Things (IoT) applications
Creation of deep learning models
MATLAB was designed with engineers and scientists in mind. These professions exist in a wide variety of industries. To better understand who uses MATLAB, check out the following chart. On the left, you’ll find industries or fields of study commonly using MATLAB. On the right, you’ll find examples of corresponding job titles.
Industries/fields of study | Job titles |
---|---|
Physics | Optical engineers use MATLAB to conduct optical design calculations like curve fitting and image processing. |
Electrical Engineering | MATLAB has specialized tools to help IoT architects and engineers design algorithms, preprocess streaming data, and deploy models to edge devices. |
Manufacturing | Control engineers can employ MATLAB in every development stage. They may use it for modeling, controller design, or to deploy control algorithms to embedded systems that require real-time tuning. |
Data Science | Data architects, engineers, and scientists use MATLAB for database management, data processing, and data cleaning. Other relevant programming languages for data science careers include Python and R. |
You can get started on your own by accessing MATLAB through the organization you work for or the university you attend if you’re a student, faculty member, or researcher.
MATLAB is a licensed product, so you’ll have to pay to use it in most cases. If you want to try running some basic MATLAB code or get a feel for the environment without spending money, consider using the basic version of MATLAB Online.
Those who want professional training or guided learning may enroll in an online course or specialization. Below are a few recommendations and resources for learners who wish to try self-instruction.
Introduction to Programming with MATLAB. This beginner-level online course can be completed in just 35 hours. It takes you through the basics of handling different data types in MATLAB and covers fundamental programming concepts like control structures and functions. By the end, you’ll earn a career certificate to share on LinkedIn or add to your resume.
Exploratory Data Analysis with MATLAB. In this beginner-level online course that takes about 19 hours, you’ll practice creating customized data visualizations, extracting subsets of data, and using interactive tools to analyze it. You can earn a career certificate for completing this course.
Predictive Modeling and Machine Learning with MATLAB. This 22-hour online course is best suited for intermediate learners. You’ll use applications to train machine learning models and apply the entirety of a machine learning workflow, from data cleaning to model evaluation.
MATLAB Central. You can read blogs and exchange code with this extensive online MATLAB code repository.
MathWorks videos and webinars. With over 6,000 options, you’ll be able to find many of the answers you’re looking for using this extensive MATLAB video library.
MATLAB documentation. You can find release notes, installation help, books, and more in MATLAB’s online documentation.
You can start building your MATLAB skill set today by enrolling in a beginner-friendly online specialization like Practical Data Science with MATLAB. Covered course content includes creating machine learning models, calculating statistics within your data groups, and learning to create interactive documents to share your reports with others.
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This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.