Which Is A Better Choice For Your Career: Python Or MATLAB?
By John Oncea, Editor
Python and MATLAB are valuable for an electrical engineer's career, but the better choice depends on your field, industry, and career goals.
Electrical engineers face many challenges: dealing with procurement, navigating component shortages, company politics, decisions made by those unaware of all the details, unrealistic schedules, constant meetings that prevent you from working on your deliverables … the list goes on.
Then there are all the choices. What components should be used? What data is important? Considering power and consumption efficiency, what are the appropriate voltage and current levels for a circuit?
You’re on your own when making those choices, but there is one I can help you out with: Which is better – Python or MATLAB? Both are powerful tools for numerical computation and data analysis but differ significantly in their nature, ecosystem, and target audience.
So, which is the right tool for you? We’ll get to that, but first, let’s explore what each took is, as well as the pros and cons.
What is Python?
Python is a high-level, interpreted programming language renowned for its simplicity and versatility. Created by Guido van Rossum and released in 1991, Python emphasizes readability and ease of use, making it an outstanding choice for both beginners and experienced developers.
According to the Python Software Foundation, Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Its extensive standard library and vast ecosystem of third-party packages establish it as a dominant force in fields such as data science, machine learning, web development, automation, and embedded systems.
Python is widely utilized in engineering, finance, cybersecurity, and AI research, thanks to frameworks like TensorFlow, PyTorch, NumPy, SciPy, Pandas, and Scikit-learn. Additionally, its integration with other languages (C, C++, Java) and compatibility with embedded systems (MicroPython, Raspberry Pi) further enhances its appeal in hardware development.
Unlike MATLAB, Python is open-source and free, making it accessible to a broader audience. Companies such as Google, NASA, and Tesla leverage Python for AI-driven applications. Due to its increasing demand in the job market, many engineers and scientists are transitioning from MATLAB to Python.
What Is MATLAB?
MATLAB (MATrix LABoratory) is a proprietary numerical computing environment developed by MathWorks. First released in 1984, MATLAB is widely used in engineering, scientific research, and academia for tasks involving numerical computing, simulations, and data analysis.
MATLAB is particularly powerful for control systems, signal processing, robotics, and power system analysis due to its built-in toolboxes, including:
- Simulink (for system modeling and simulation)
- Control System Toolbox (for designing controllers)
- Signal Processing Toolbox (for analyzing signals and filters)
- Optimization Toolbox (for solving complex mathematical problems)
MATLAB uses a proprietary programming language with a syntax optimized for matrix operations, making it efficient for numerical analysis. Unlike Python, MATLAB is not open-source and requires a paid license, which can be expensive for individual users.
Despite Python’s increasing popularity, MATLAB remains a standard tool in many engineering disciplines, particularly in academia, automotive, aerospace, and biomedical fields. Industries such as NASA, Boeing, and Siemens continue to use MATLAB for high-precision simulations.
What Your Peers Are Saying
Which tool you choose largely depends on your field and specific career goals, an idea underscored by engineers on various Reddit threads. For instance, here’s what they are saying about Python:
- Versatility and Popularity: Python is widely regarded as a versatile language used in various fields including web development, data science, machine learning, and more. “Python is ultimately much more versatile and more common professionally.”
- Industry Standard for Machine Learning: Python frameworks like TensorFlow and PyTorch are the gold standard in the industry for deep learning. “TensorFlow/Keras and PyTorch are the gold standard for deep learning frameworks within the industry, and these are both Python frameworks.”
- Cost-Effective: Python is open-source and free, making it accessible for both individuals and companies. “Python is also open source and free whereas MATLAB is not.”
- Community and Resources: Python has a large community and extensive resources, which can be beneficial for learning and troubleshooting. “Python is a general-purpose language, so it can be used for many things, but when it comes to specific tasks, domain-specific languages like MATLAB may be easier to use.”
In comparison, here’s what they are saying about MATLAB:
- Specialized for Engineering and Academia: MATLAB is highly specialized for numerical computing and is widely used in academia and engineering fields. “MATLAB is great for undergrad stuff. Any numerical method an undergrad might want to explore can be done more easily in MATLAB than any other language I know of.”
- Rapid Prototyping: MATLAB is excellent for rapid prototyping, especially in fields like control systems, signal processing, and image processing. “MATLAB is very good for rapid prototyping for a variety of applications.”
- Industry Use in Specific Fields: MATLAB is still prevalent in certain industries like automotive, aerospace, and academia. “In Germany, if you search in LinkedIn, many industries (robotic, automotive) hire engineers with Matlab+Simulink experience.”
- Licensing Costs: One of the major drawbacks of MATLAB is its cost, which can be prohibitive for smaller companies or individual use. “The problem with MATLAB is the license fee. It's ok when you work for a university or big institution where they pay for the license.”
MATLAB is often viewed as a specialized tool for matrix operations and technical computing, with a user-friendly interface for tasks like data visualization and algorithm development. Python, in contrast, is recognized as a general-purpose programming language that, with libraries like NumPy and SciPy, can perform many of the same numerical and scientific computing tasks as MATLAB.
Some find MATLAB's interface intuitive, making it easier to start with for certain tasks while Python’s versatility and widespread use have fostered a large, active community, providing extensive resources and support for learners.
When it comes to performance and efficiency, MATLAB is often noted for its speed in matrix computations and numerical tasks though Python’s performance in numerical computations has improved significantly with the development of optimized libraries like NumPy.
If cost and accessibility are issues, MATLAB requires a paid license and Python is open-source and free, making it accessible to a broader audience. Finally, MATLAB offers specialized toolboxes for various applications, such as Simulink for modeling and simulation, which may not have direct equivalents in Python. Python has a vast ecosystem of libraries that cover a wide range of functionalities, though some specialized MATLAB toolboxes may not have direct counterparts.
Which Should You Choose
Both Python and MATLAB are valuable, but the better choice depends on your career goals and the industry you’re targeting. If you want broad versatility and better integration with modern software and data science tools, Python is likely a more valuable tool.
If you are focusing on fields that heavily rely on specialized numerical analysis, simulation (especially with Simulink), or you’re in an academic/research setting where MATLAB is predominant, then MATLAB might be more immediately useful.
Many electrical engineers end up using both. Starting with Python can offer broader opportunities and future-proof your skills, while MATLAB can be essential for niche, technical problems. Balancing both – using MATLAB for its specialized toolboxes and Python for its versatility – could be the ideal approach for a robust engineering career.