The biggest challenge today is to prepare graduates for Industry 4.0 jobs. While no one can clearly define which roles will cease to exist and which ones will be created, experts advise students to be adaptive and upskill in domains that will shape the jobs of the future. In this regard, data science is one of the emerging fields that has a huge gap between demand and supply and will be imperative across disciplines. “Today there is no shortage of data or computing abilities but there is a shortage of workforce equipped with the right skill set that can interpret data and get valuable insights,” said James Abdey, assistant professorial lecturer Statistics, London School of Economics and Political Science (LSE), on the sidelines of Annual Teacher’s Symposium. He added that data science is a multidisciplinary field that draws from Mathematics, Economics, Finance, Statistics, among other subjects.
“There is no barrier on who can become a data scientist. The necessary skills needed in the domain include analytical thinking and decision-solving as well as decision-making aptitude, he said. On future-proofing the jobs of tomorrow, Jitin Chadha, founder and director, Indian School of Business and Finance (ISBF), said, “As everything becomes data-driven, acquiring analytical and statistical skill sets will soon be an imperative for all students, including those pursuing Social Sciences or Liberal Arts and also for professionals.”
While outdated curriculum and the dearth of trained faculty in fields such as Data Science and ML is a major roadblock towards preparing graduates for Industry 4.0, Chiraag Mehta, associate director, (ISBF) says an effective solution would be to increase international collaborations and deeper industry-academia connect to bring the best practices to the classrooms. “With international collaborations, higher education institutes can bring in the latest curriculum while a deeper industry-academia connect including, guest lectures from industry players and internships will help students relate the theory to real-world applications,” said Mehta.