Upskilling: Identify and learn transferable skills

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June 28, 2021 4:00 AM

NIT professor suggests how tech students can upskill themselves

“However, before focusing on the underlying principles, students tend to operate only at the application and technology layers of this stack and end-up learning the syntax cum nitty-gritty of a couple of AI frameworks/tools.”“However, before focusing on the underlying principles, students tend to operate only at the application and technology layers of this stack and end-up learning the syntax cum nitty-gritty of a couple of AI frameworks/tools.”

Recently, a global report caused a stir in the Indian information technology (IT) industry; it noted that with automation taking place at a fast pace across industries, especially in the tech space, Indian software firms that employee over 16 million people are set to slash headcounts by 3 million by 2022.

While industry body Nasscom was quick to refute that—and said the IT industry continues to be a net hirer of skilled talent, and that top-5 Indian IT companies are planning to add over 96,000 employees in 2021-22—it doesn’t take away the fact that, to stay relevant in their job, IT employees need to constantly upskill or reskill themselves.

Computer science/IT students

At the same time, should IT students who will enter the job market in 2022 also start making themselves multi-skilled instead of focusing on one particular area? Karthick Seshadri, assistant professor and head, Department of Computer Science and Engineering, NIT Andhra Pradesh, has some suggestions on how current students can upskill themselves.

Top layers vs. bottom layers

“In computer science and IT, just like any other engineering domain, there are four vertically-stacked layers across which one needs to develop skills,” Prof Seshadri said. “These layers, from the bottom to the top, are theory, systems, technology and applications. Arguably, the rate of evolution of the top layers is more rapid as compared to that of the bottom layers. However, the skills gained in the bottom layers are typically transferable and provide a strong foundation to comprehend and adapt to the rapidly-evolving higher layers.”

Underlying principles

Many students, he added, tend to overlook this and attempt to go behind jargons and trends in the top-level layers of this stack without paying much attention to grasp the underlying principles in the bottom layers. “For instance, a thorough foundation in probability, statistics, calculus, optimisation theory and linear algebra will impart significant advantage and adaptation skills to a student in developing state-of-the-art AI/ML based models and systems,” he said. “However, before focusing on the underlying principles, students tend to operate only at the application and technology layers of this stack and end-up learning the syntax cum nitty-gritty of a couple of AI frameworks/tools.”

Transferable skills

Subsequently, he added, due to the rapidly-evolving nature of the upper layers, when the tool is superseded by another tool, the skills learnt become obsolete, and such students will be at a greater risk of lay-offs. “The trick is to realise this intricate dependency among the layers; identify and learn transferable skills to stay relevant in a rapidly evolving industry. To sum-up, practising a kinaesthetic learning approach to gain multiple transferable skills in the following domains holds the potential to significantly help the graduating batch of 2022: AI, data analytics, ML, blockchain, IoT and cloud computing.”

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