New technologies like MATLAB make it easy for engineers, scientists, data scientists, and financial analysts to do complex computer simulation and modeling. Imagine designing an engine and visualizing it in a 3D computer simulation to test how the engine functions underwater or in outer space.
MATLAB, a high-level programming and simulation environment for scientific computing, enables you to visualize and analyze data in real-time. Its highly flexible interactive mode also allows you to continuously change simulation parameters. Advanced math skills used to be necessary for this kind of complex modeling, but with programs like MATLAB, you no longer need to be a math whiz.
MATLAB’s scientific programming language lets you bypass advanced math skills because the computer solves and simulates the equations (like the physics of zero gravity in space) and then provides a powerful 3D visualization of your engine functioning in outer space. What used to be time-consuming and impossible to do on paper is now easy to conjure up with a few lines of code.
What’s more, the MATLAB programming language is easy to learn. For example, if you took a one-week programming course on C, you still would struggle to read and write code. But if you take a one-week course on MATLAB, you will quickly be able to read and write the MATLAB code.
Engineering & design, big data analysis, financial modeling, and scientific research are some of the ways MATLAB is being applied in the business world.
MATLAB stands for “matrix laboratory” because it’s optimized for working with matrices. A matrix is a multi-dimensional data structure. Modern data science operations are implemented using matrix operations based on linear algebra. This might include financial modeling at an investment bank or data mining for neuroscience research.
However, MATLAB is not the only scientific programming language. Octave is a free, cross-platform, and has much of the same functionality as MATLAB. Python is also becoming increasingly popular, although MATLAB remains the top choice when it comes to complex data science and 3D data visualizations.
The decision to go with MATLAB or Python is much like the PC vs. MAC debate. Almost everything you can do in one language, you can do in the other. However, there are some key nuances on which language to choose, depending on your project.
MATLAB is great for complex online interactive data analysis and visualizations like engineering simulations. MATLAB enables you to continuously access the data and make constant changes to the simulation code. It’s a better testing environment for something like a newly-designed engine.
Python is optimal if you want to process a lot of data, but don’t need to visualize or tweak it. For example, Python is a great tool for conducting mega data-crunching behind the scenes. This might be running large neuroscience data sets that monitor electrical activity in the brain. Once the model is set up, Python can run it in the background. Python can also create 3D visualizations, but MATLAB’s visualization interface is more user-friendly and interactive.
MATLAB is developed by a company called Mathworks. All the coding is done in-house and as a result, the code is internally more consistent. Python, on the other hand, is free and open source. Thousands of people contribute code and tools to Python code libraries. For example, you might borrow someone’s code but then discover it doesn’t work in a newer or older version or conflicts with other Python toolboxes. There is less consistency, which can cause headaches or unexpected results.
As mentioned above, MATLAB is easy to learn and has a low barrier to entry. However, there are still some important skills that every MATLAB programmer should master.
Program effectively. Learning how to program effectively can mean the difference between your data analysis taking a few seconds versus multiple hours to run. I’ve seen many people complain about the “slowness” of MATLAB. However, if you clean up the code, your data analysis can run many times faster.
Problem-solving. Perhaps the most important set of skills is a clear understanding of the problem you’re trying to solve. Anyone can write a line of code. But it takes careful practice and training to gain expertise in solving data analysis problems. Fortunately, these skills can be learned, which is something I stress in my courses.
Here are 3 of my courses on Udemy for Business to help you and your team hone essential MATLAB skills.
1. Learn MATLAB Programming, Debugging, and Style. Start by learning what it takes to be an effective MATLAB programmer and what separates an expert from a novice.
2. Complete Linear Algebra Theory and Implementation. The second step is to become well-versed in linear algebra, which is the most important branch of mathematics for computation sciences, including machine learning, AI, data science, statistics, simulations, and so on.
3. Master MATLAB through Guided Problem-Solving. Take your MATLAB skills to the expert level by learning how to solve real-world problems in MATLAB. This course has 40 hours of instruction on hands-on applications with varying levels of difficulty, including over 160 problem-sets that are presented and then solved.
Computer simulation and modeling tools like MATLAB are evolving every day. New technologies will enable us to do more, with less effort. The key for any employee is to continuously stay on top of the latest technologies and new programming languages.
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