With technology leading innovation in every field, how will it pan out in Indian education system? An incentive system pulling the best tech talent into software development rather than more cutting-edge areas would mean the country would reach a saturation point soon.
When Rahul Dave, who was teaching data science and AI/ML at Harvard University, went to one of the Indian Institutes of Technology some time back, he was somewhat nonplussed.
He was talking to a group of mining engineering students about exciting new possibilities in using artificial intelligence/machine learning (AI/ML) for oil exploration. His pitch to them was that their value to oil companies would rise steeply if they were to add AI/ML on top of their core engineering discipline. “And they were like, ‘Nah, we’re going to become software developers," says Dave, who was bemused because he had seen in the US how the demand for AI/ML analysts had already spiked in a variety of fields.
Subhendu Panigrahi, co-founder of Skillenza, which helps companies hire tech talent by running online challenges and hackathons, is not so surprised. “Roles like software developers and full-stack engineers are always in demand, and even more so after covid as every organization wants to digitize their workplace. So, a lot of young techies in India just want to become full-stack engineers and join a multinational company," he says.
“They’re not sure they can land good jobs so easily in data science. You can also see this in the bootcamps that companies are launching in Bengaluru. They’re mostly for software developers and full-stack engineers and not machine learning or data analytics bootcamps."
An incentive system pulling the best tech talent into software development rather than more cutting-edge areas would mean the country would reach a saturation point and never rise beyond that level. But he had a different experience when he ran a data science bootcamp in Bengaluru prior to co-founding Univ.ai, an online platform for teaching AI - currently only for students from India.
“The students who came for the first bootcamp - most of whom were not from the IITs - had a hunger to learn. A number of them later became TAs (teaching assistants) at Univ.ai and they’re super good and actually better than the TAs I had in Harvard," says Dave. “So, the talent pool is definitely there, but it’s not being developed in a great fashion. Once I realized this from the bootcamp, I was totally sold on the idea of doing Univ.ai."
Skillenza is also seeing the winds of change blowing. “A job description opening up in a lot of companies is data engineering. So, we’re going to build a bootcamp around it, working with the industry to develop the curriculum and find the faculty," says Panigrahi. “Full stack development is the staple, like dal-rice. Then you add vegetables to make the meal complete. Data engineering is one area which we think will become huge in the coming days."
Data engineer is the one who writes code to handle gigabytes of data coming from social media posts or video cameras or geolocation tracking of phones or sensors on machines. He formats the data to make it easier for an AI engineer to build analytical models for it. So, the two go hand in hand. Bootcamps like that of Skillenza reflect the gaps in tech education in India.
(This is a slightly modified version of an article originally published in Live Mint. The original article can be found at https://www.livemint.com/news/are-tech-schools-in-india-preparing-students-for-the-ai-ml-age-11618134198731.html)