Indian Universities Desperately Need to Update Their Outdated CS Curriculum
Several Indian students today aspire to become AI experts—building cutting-edge models, mastering ML algorithms, and staying on top of global research trends. The desire is largely fuelled by the global AI wave and the dream being sold at Indian schools and universities, which are all introducing AI and ML in their curricula. AIM Research recently published a report on the top 50 institutes offering AI courses in India 2025, highlighting how universities are increasingly introducing courses for AI in master’s programmes. This is driven by the increasing industry demand and corporate partnerships for providing students with real-world applications of AI/ML and upskilling them with the relevant skills for the industry. However, according to several industry experts, the curriculum of Indian universities offering these courses in their regular computer science fields seems out of place. There is a big mismatch between the curriculum and what the industry demands. How Much is Too Much? BITS Pilani campus group vice-chancellor V Ramgopal Rao told AIM that while AI is being introduced in many universities, it often lacks depth. Topics like deep learning, reinforcement learning, and advanced AI applications are either optional or lightly covered. “There is limited focus on hands-on projects or exposure to real-world problems, which are essential for AI development,” Rao said. “AI is a fast-evolving field, and the lack of emphasis on research and innovation within the curriculum limits students’ ability to contribute to global advancements.” He emphasised that AI requires knowledge of fields like cognitive science, ethics, and domain-specific expertise (e.g., healthcare, finance), which are rarely integrated into CS programs. “Universities need to partner with industries to include hands-on AI projects, internships, and exposure to real-world applications within the existing framework,” he said. Similar sentiments were expressed by Chiranjib Sur, a visiting professor of computer science at Krea University in Andhra Pradesh, who told AIM that the current curriculum on AI in most universities focuses on using Python libraries to build AI models. That needs to change. “I think that we need to calibrate the courses and teach more foundational things,” Sur said, citing the importance of teaching the science and mathematics behind those libraries and how to build them. This will ensure that the students and the professionals know which techniques to use for different problems. Sur said that a stronger emphasis on fundamental mathematics in combination with core knowledge of computer science (systems, architecture, compilers etc) is essential. “While I teach computer science or some AI techniques, the focus is to learn those techniques and solve domain-specific problems,” he added, highlighting the need for learning fundamentals of CS like mathematics and not just AI applications. Ritvik G, a graduate research assistant at the Artificial Intelligence Institute of South Carolina (AIISC), told AIM that the curriculum followed across Indian universities places a heavy emphasis on classroom-based learning and theoretical exams, with limited attention to practical lab work or real-world projects. “AI-related courses generally focus on traditional topics like NLP, computer vision, and algorithms. However, foundational architectures for advanced AI workloads, such as neural architecture search, enterprise AI or neuromorphic computing, are rarely part of the curriculum,” he said. Ritvik further pointed out that the education system was set up to churn out developers and individuals focused on getting jobs rather than adapting to the evolving needs. “Four exams that centred around a book and few slides rather than intuitive thinking, where anything outside of their answer key is regarded as the wrong answer with no score provided for anything close but perfect,” he added. There is definitely a shift needed in the CS degrees in Indian universities. “Teach math, statistics, programming fundamentals, and soft skills in the first year.  The second year should be all about various projects using GenAI tools. Problem-solving is more important than coding,” said Naveed Iftikh, co-founder of AtomCamp. Should Indian Universities Offer a Different Course for AI? “I’ve noticed many colleges introducing separate ‘AI & ML’ branches, like an exclusive department apart from Computer Science. The syllabus? 80% the same as CS, with just some buzzwords like ‘Neural Networks’ and ‘TensorFlow’ added,” Chaitanya Athukuri, product manager at Nielsen, said in a post on LinkedIn. He added that though AI and CS are not intrinsically separate fields, the education providers are able to sell it well. Meanwhile, many AI experts recommend that people study computer science and take a crash course in generative AI, if necessary. There are differing voices too. Amit Sheth, the chair and founding director of AIISC, told AIM that he believes that AI has advanced and expanded so much in this century that it is no longer ideal to have it as a part of the CS curriculum. “In my opinion, it is necessary to offer degrees and skills-based certifications in AI, in addition to CS. In a four-year program, it may be appropriate to have one or two years in common, but there is so much to learn at foundational, translational, and application levels in AI,” Sheth said. Priyankar Kumar, a software engineer, said that the curriculum is largely the same worldwide—the problem is that it focuses on exams instead of practical applications. AIM spoke to two recent CS graduates from the RNS Institute of Technology in Bengaluru, who agreed that the new AI curriculum was not up to date with the current industry requirements. They said that though there is a separate AI-ML branch in BTech, the curriculum often overlaps. At the same time, they believe that the two separate branches are necessary as the topics differ starting the second year of college. Similarly, Adarsh Shirawalmath, the founder of Tensoic, had earlier told AIM that though his college has been helpful, it is still years behind when it comes to the type of research that is being pursued there. According to several online forums, people want to study AI, ML, and data science in their BTech classes but always find the curriculum outdated. Moreover, several students also question the idea of AI as a separate discipline, as the course is very similar to the CS major.
Several students also question the idea of AI as a separate discipline, as the course is very similar to the CS major.
The curriculum of Indian universities offering AI courses in their regular computer science fields seems out of place.
["AI in Education"]
["AI in Education", "data science", "GenAI", "artificial intelligence", "AI", "neural network", "ML", "computer vision", "NLP", "deep learning", "generative AI"]
["AI", "artificial intelligence", "ML", "deep learning", "neural network", "NLP", "computer vision", "data science", "generative AI", "GenAI"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.