on September 18th, 2019

The ability to code in the python language is becoming an increasingly sought-after skill, particularly in the engineering field. In industries underpinned by computer programming, this skill is critical for data analysis and visualizations, artificial intelligence and machine learning, and automation.

Knowledge of python is pertinent with traditional engineering tasks changing across disciplines, as computing technologies transform the way engineers do their jobs. Coding is becoming a much sought-after skill by employers around the world.

In 2016, Burning Glass Technologies suggested that seven million job openings in 2015 were in occupations which valued coding skills. Their report, titled ‘Beyond Point and Click: The Expanding Demand for Coding Skills,’ also predicted that by 2030, 500 billion devices would be connected to the Internet of Things. Therefore, the job openings which value coding skills will likely rise to levels unforeseen back in 2015.

“We live in a digital world. Our phones, our cars, our banks, and our hospitals - nearly aspect of our lives - depend on computer code,” the report stated.  

“As a result, coding or computer programming, is becoming a core skill requirement for many well-paying jobs. Coding skills are in-demand across a broad range of careers, not just for programmers.

Source: Burning Glass Technologies

“The ability not only to use but also to program software is often required of business people who work with data, of designers and marketers who create websites, of engineers who build products and technologies, and of scientists who conduct research.”

With python’s abilities to disseminate and crunch data, the language makes the perfect candidate for overseeing industrial environments. In such settings, you could have many software and hardware elements that need to be controlled in unison. For example, python allows engineers to implement open source SCADA (Supervisory Control and Data Acquisition) systems that can perfectly sync an industrial project.

The coding language can handle large data sets that engineers can develop algorithms around, to meet the ends they require for their setups. Therefore, it is a particularly useful language in machine learning realms. Machine learning focuses on developing systems that can warp and transform around the injection of data into a system — and learn from it. It is being utilized in several industries, which are looking to automate some of their more repetitive tasks to free up their workers and direct them towards more productive tasks.

Python can also be used to actively teach a machine what to look for in a set of input and output data. This alerts personnel when a system breakdown has occurred or when part of a system requires maintenance. In the machine learning world, this is referred to as supervised learning.

Unsupervised learning involves a machine learning from the input data of hundreds of similar projects and putting together a python-activated algorithm that can find and classify the data you want the machine to learn from in your system.

Python is convenient for engineers due to an extensive library of available pre-written code that can quickly be expanded on and implemented within a system. There are over 14,000 python packages available for download, making it a more accessible language than some of the alternatives that need to be coded from scratch. Python also takes up less space than alternative programming languages.

The standardization of the language is what is making some of the biggest businesses all around the world (JP Morgan, IBM, and more) utilize python on their websites and inside their enterprises. Consequently, engineers are being asked to understand more and more of the programmed backend of the companies they are working within. No longer can one set of skills suffice.

The Engineering Institute of Technology is hosting two three-month-long live, online professional development courses in python programming. One of them focuses on python programming and its application within the different engineering fields. The second course looks at how advanced python programming can be used within machine learning algorithms.


Works Cited

“Real-Time Job Market Analytics Software.” Burning Glass Technologies, www.burning-glass.com/.

“Why Engineers Are Learning Python.” LinkedIn, www.linkedin.com/pulse/why-engineers-learning-python-koen-van-viegen.

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