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regular-article-logo Friday, 22 November 2024

Stream And Consciousness

Things one must consider before opting for an engineering course

Jagannath Banerjee Published 05.07.22, 04:10 AM
Aspiring engineering students should find out whether and how far these courses are relevant to the current job market.

Aspiring engineering students should find out whether and how far these courses are relevant to the current job market. Shutterstock

July is the season of aspirations. Young boys and girls on the verge of adulthood are busy choosing their future paths. The engineering course most in demand for the last several years is computer science and engineering. One of the primary reasons is the belief that it yields maximum job opportunities.

So what happens when you don’t qualify? Of late, the trend has been to settle for any course associated with computers. As a result, students get lured into newly-minted courses that may not even have a curriculum approved by the All India Council for Technical Education (AICTE).

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Aspiring engineering students should find out whether and how far these courses are relevant to the current job market. Are top recruiters hiring from these new launches? A quick look at the eligibility criteria of top information technology (IT) companies — ones that employ the largest numbers every year — will reveal that the traditional streams are still preferred.

The strong need for fundamentals can also be deduced from an analysis of the problem statements submitted by various industries to AICTE’s Smart India Hackathon. While the problems are to be solved “using” certain technologies, the actual solution needs in-depth knowledge of science and engineering. After all, how can an engineer apply something he or she cannot understand? Tools such as machine learning (ML) or artificial intelligence (AI) are meaningful only when used appropriately. But if someone were to only know the tool and not why and where it is applicable, such knowledge would be utterly superficial and useless in the long run.

Unfortunately, the curriculum and syllabi of certain new courses provide limited scope to learn application.

Furthermore, it is erroneous to imagine that ML, AI and Internet of Things (IoT), etc. are aligned only to computer engineering. They are tools that are relevant for all branches of engineering.

In fact, it is estimated that by 2025 the largest demand for a digital workforce will be in manufacturing industries. Thus, it stands to reason that opting for mechanical or electrical engineering at a college that offers supplementary courses in ML, AI, etc. is wiser.

The industry does have an unmet demand for skilled personnel in Industry 4.0 technologies, or the way companies are revolutionising the way they manufacture, improve and distribute their products. Smart factories are equipped with advanced sensors, embedded software and robotics that collect and analyse data and allow for better decision-making. But the operative word is “skilled”. A piece of paper claiming that an engineer has a degree in Industry 4.0 technologies does not necessarily mean that he or she is actually skilled. A well-designed curriculum, expert faculty and adequate infrastructure are the bedrock of any course.

Most universities or colleges that offer new bachelor of technology (BTech) degrees in Industry 4.0 technologies are actually the ones that encash the hype surrounding jargon such as ML and AI.

The one thing an engineering student cannot overlook is a strong foundation — yet it is the basics that are often overlooked in these newly-minted branches. If a student is exposed to too many highly complex subjects, would he or she be able to learn anything in-depth? And can anything be developed when the foundation itself is not stable? Adequate time and effort should be first given to core courses that will create a firm basis for the student’s future professional career. Afterwards, it is always possible to take up a minor or honours in emerging areas.

For that matter, these tools can be learnt from short-term certification courses too. On the surface, the label of machine learning or artificial intelligence may seem attractive; but, in the long run, knowing a tool without really understanding how it works and where it can be applied can be really disastrous.

Therefore, before following every new trend marketed to you, do due diligence. Also, remember to look beyond immediate benefits.

The writer has been in the field of engineering education for over two decades, and is founder and chairman-trustee of the Academy of Technology, Adisaptagram, Hooghly

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