Gone are the days when students fancied a computer science seat in a top tier college. Now there is a demand for specialisation. Thanks to the hype around artificial intelligence (AI), many Indian institutions are now racing to offer their own B.Tech programmes in AI. Some of the notable colleges currently offering bachelor programmes in AI include IIT Hyderabad, Great Lakes International University, GH Raisoni College and others.
In the last few years, the demand for professionals equipped with skills in AI, machine learning, cloud computing and cybersecurity has continued to remain high. Each stakeholder, from the government to faculty to students, are now realising the importance of honing skills in these digital technologies to accelerate career progression. According to the National Employability Report for Engineers by Aspiring Minds, nearly 80 percent of engineering graduates lack the requisite skills to be considered employable; and only 3 percent possess skills that are needed for jobs in emerging tech such as AI, machine learning, etc.
“I am all in for institutions introducing career-critical skills as part of specialisation in the regular degree programmes,” said Arjun Nair, co-founder of Great Learning.
Recently, Great Learning has started offering UGC recognised degree programmes in MBA, MCA, M.Tech and BBA, along with top Indian universities including SRM University, JAIN (Deemed-to-be University), Shiv Nadar University and PES University in new-age specialisations like data science, artificial intelligence, machine learning, cloud computing, big data analytics, data engineering and digital marketing to help learners score lucrative jobs opportunities.
The director of the Master of Artificial Intelligence in Business (MAIB) at SP Jain School of Global Management, Debashis Guha, told Analytics India Magazine that he believes in the need for bachelor degree programmes in AI as it is essential to fill the demand-supply gap for AI engineers. “AI is going to be implemented in all industries and sectors, and we need AI engineers who are going to lead this technological transformation,” he added.
While the US and China are ahead of their time, India is still in its early days of incorporating AI into their curriculums. Two years ago, the Chinese Ministry of Education gave 35 higher education institutions the go-ahead to set up undergraduate AI programmes in the country.
In 2003, the Indian government had started the national programme on technology enhanced learning (NPTEL) in partnership with premier institutions like IIT and IISc. NPTEL offers online courses in science and engineering at university and research levels. Under computer science and engineering discipline, the platform offers various courses in AI, data science and machine learning.
“Just because a particular specialisation is in demand does not mean that we start B Tech courses in them. One of two courses in the final year of BTech is quite sufficient to learn enough AI to fit into most industry profiles,” wrote Ashish Sahani, assistant professor at IIT Ropar, in a Linkedin post.
Further, Sahani said options for such graduates would be limited. He suggested that a computer science or electrical engineering graduate with few courses of AI under their belt will have much broader options in the job market than someone with a ‘B Tech in AI.’
Currently, many universities such as Purdue, UCLA, Imperial College of London, etc., have all created bachelor programmes in data science, machine learning, and artificial intelligence. Meanwhile, other universities have considered AI as a subject at a Master level and not bachelors. IIT Bombay, IIT Kharagpur and other universities are some of the few universities in India that are offering Master’s programmes in AI.
“One would argue that you can pick up those basics in a typical computer science and later do an advanced specialisation in AI,” said Mausam, professor at IIT Delhi. However, when it comes to the market per se, AI is becoming super important. As a result, many universities are starting these kinds of undergraduate and bachelor programmes in AI, where a student can join the relevant departments or research field right away.
A bachelor’s degree in AI prepares students to build applications like speech recognition, facial recognition, and language translation. The area of study may include data science, machine learning, advanced mathematics, statistics, engineering, robotics, ethics, etc. Guha said AI needs to be part of the curriculum in almost all university departments, especially in the natural and social science departments and engineering schools.
For instance, Colby College, a liberal arts college in Waterville, Maine (USA), introduced AI in nearly all disciplines, from computer science to English literature, in addition to specialised degree programmes and research in the field of AI. Another example, Carnegie Mellon University, one of the leading universities in Pittsburgh, Pennsylvania (USA), which has integrated instruction in AI and technology into its entire MBA programme. It is also one of the world’s leading centres of education and research in the field of artificial intelligence.
At S P Jain School of Management, the management has been following a similar route. “AI and related fields have been integrated into our MBA program, and in addition, we offer a degree that dives more deeply into the subject of AI,” said Guha.
Both serve different purposes. A B.Tech or B.E degree in AI aims to train students to work as AI engineers and develop AI applications and tools or do AI research. The inclusion of basic AI material in another programme, however, ensures that students will know when to use AI tools and techniques, which ones to use and how to use them, etc.
Drawing a parallel, Guha said that the B.Stat students are trained to be professional statisticians. ‘Statistics courses, on the other hand, are taught in business schools, social science departments, engineering schools, etc., for students who will need to use statistical tools and techniques in their own work,’ he added.
Great Learning’s Nair said if a student is planning on a core technical career, where the aspiration is to work on cutting edge AI applications, they will need to specialise in AI. But, on the other hand, if they intend to be on the periphery and implement AI applications or use AI applications for business impact, then a few courses might be enough.
Further, he said that learners would evaluate parameters such as accessibility, flexibility, career support, curriculum, and industry relevance before enrolling for a programme, whether it is a B Tech in AI or any other AI programme being offered.
“It is important to ensure that program credentials offered by any institution should consist of a well-structured curriculum, power-packed with industry-relevant case studies and projects, mentored sessions and enough handholding to achieve a thorough understanding of the concepts. Keeping in mind these pointers can help learners make an informed decision and choose the best-suited learning program for themselves,” said Nair.
Currently, every learning institution is aware of the importance of imparting career-critical competencies to their students. The major challenge, however, is the lack of trained faculty in new-age skills. Thus, hiring or upskilling existing teachers becomes crucial to deliver world-class education in fields like AI, analytics, machine learning, and cloud computing.
Universities also regularly consult with industry experts regarding relevant trends to prepare a more robust and up to date curriculum. “It is this high-quality education that ultimately helps students and professionals power ahead in their careers,” said Nair.
Many industry experts believe that all science and engineering departments need to teach the basics of AI, especially machine learning and decision making, with electrical and mechanical engineers learning more advanced topics. Plus, all social sciences will have to teach basic AI and some advanced topics that vary by department. Humanities do not need AI yet, but this could change. “The basic ideas of AI should be introduced early in the program, and electives can be introduced later,” said Guha.
Some argued saying, if you take AI as multidisciplinary, then AI should be a Master’s programme. If you think AI has become a separate discipline, you will have to bring in other knowledge from domains like cognitive sciences, neuroscience, etc. Then, AI can be a different degree in itself. “In a few years, we will get to know whether AI establishes itself as an independent discipline or an important multidisciplinary field,” said Mausam.
Amit Raja Naik is a senior writer at Analytics India Magazine, where he dives deep into the latest technology innovations. He is also a professional bass player.
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