The Central government is working with industry partners to revamp the AI curriculum, including in B.Tech Computer Science programs, across Indian educational institutions. This initiative aims to enhance practical learning opportunities, improve faculty preparedness, and establish a more adaptable learning path for students. Union Minister for Electronics & IT, Ashwini Vaishnaw, recently chaired a high-level meeting with the AI Curriculum Taskforce to discuss these changes.
The Taskforce, in collaboration with industry experts and the National Association of Software and Service Companies (NASSCOM), conducted a detailed study on the existing B.Tech Computer Science curriculum. While acknowledging the expansion of AI coverage in Indian education, the study highlighted significant gaps in teaching methods, infrastructure, and practical exposure in areas like Generative AI, Machine Learning Operations (MLOps), and foundational model development.
Recommendations from the study include transitioning from traditional lecture-based teaching to a more practical approach anchored in real industry use cases starting from the first semester. It also suggests integrating AI courses into the academic credit system with a structured semester-wise implementation and increasing practical exposure to 40-75% based on the degree and specialization.
The proposed changes also emphasize the integration of Responsible AI and AI Governance throughout all semesters rather than as standalone modules. Additionally, a flexible learning pathway is suggested, offering a Certificate after Year 1, a Diploma after Year 2, and an Advanced Diploma after Year 3. Faculty development is a key focus, with plans for structured training programs, curated course content, standardized assessments, modernized labs, and the involvement of experienced industry professionals as adjunct faculty.
Participants in the discussions also recommended the establishment of a national-level shared AI infrastructure, supported jointly by industry, the Government, and academic institutions. This infrastructure would ensure equal access to resources like Graphics Processing Unit (GPU) compute, edge devices, software stacks, and subscription-based platforms across various colleges and universities.
