‘AI for All’ initiative on SWAYAM Plus has drawn over 50,000 registrations, offering free courses in fields from cricket analytics to chemistry
IIT Madras is working to bring artificial intelligence education accessible to all, as they are developing a huge number of courses in Hindi through its ‘AI for all’ initiative on the SWAYAM Plus platform.
From coding labs to everyday classrooms
AI is changing the way any and every industry works and it is no longer confined by computer science meaning it could be useful not only for technologists but for teachers, commerce students, chemists, and cricket fans alike. The first two initiatives of ‘AI for all’ received a total of 50,000 registrations before a Hindi-language version launched on January 22, 2026, to reach learners more comfortable outside English.
Six courses, no coding required
The programme now runs six free, beginner-level courses — spanning education, physics, chemistry, accounting, cricket analytics, and Python-based AI/ML — using real datasets and hands-on exercises, with no prior coding background needed. Dean R Sarathi said the goal was to dispel the notion that AI is reserved for computer science professionals, while IIT Madras Director V Kamakoti noted that bilingual courses help both concepts and opportunities reach a broader national audience.
Reaching smaller cities, easing anxiety
The initiative focuses mainly on Tier 2 and 3 cities in India where technical education is less accessible. ‘AI for all’ initiative has a practical aspect of learning because learning in one’s mother tongue makes one feel confident and removes fears.
Learner feedback shapes the approach
All those who participated in the project, among whom there are two individuals hailing from different parts of India – a chemist from Mumbai and an educator from Varanasi, opined that receiving the training in Hindi made the experience look more real than theoretical in nature. At the same time, those who were taught in Hindi also gave a feedback to the organisers in relation to some errors encountered during the process which could affect the learning experience in the future while implementing these programs on a large scale.
