IIT Delhi and TeamLease EdTech Kick‑start AI for Healthcare Executive Programme

The Indian Institute of Technology Delhi has teamed up with TeamLease EdTech to introduce a 24‑week online executive programme in artificial intelligence for healthcare professionals. With live weekend sessions, hands‑on projects and mentorship from leading faculty, the course is scheduled to begin on 1 November 2025, and admissions are open until 31 July 2025.

The programme aims to equip clinicians, engineers, data scientists and med‑tech entrepreneurs with a robust understanding of AI applications across healthcare domains including diagnostics, imaging, risk scoring, hospital operations and public health analytics. Course modules cover foundational topics such as machine learning, deep learning, big data and IoT monitoring of patient data, before progressing to advanced concepts like natural language processing for electronic health records, predictive analytics and AI‑powered dashboards.

Classes will be conducted entirely online on weekends to accommodate working professionals, and participants will work with real clinical datasets and hospital data systems. A capstone project, mentored by IIT Delhi faculty and experts from AIIMS and the med‑tech industry, will enable learners to build deployable AI tools under guidance.

Fee structure is set at ₹1.20 lakh plus 18 per cent GST, payable in two instalments. Eligibility extends to any graduate professional working in healthcare, research, industry or academia with interest in AI, and no prior coding experience is required.

Officials emphasise that AI has moved from optional to essential in modern medicine. Professor Manav Bhatnagar, Head of the Continuing Education Programme at IIT Delhi, highlighted the institute’s goal to develop “next‑gen capabilities that respond to evolving healthcare needs”, adding that the programme will empower professionals to lead this transformation. Shantanu Rooj, Founder and CEO of TeamLease EdTech, noted that the collaboration bridges clinical knowledge and data intelligence to create impactful healthcare solutions.

External analysts point to broader global trends behind the move. The World Economic Forum estimates that AI could add over US $150 billion annually to global healthcare economies through enhanced efficiency and patient outcomes. In India, NITI Aayog and EY forecast the digital healthcare market—driven by AI diagnostics and telemedicine—to exceed $37 billion by 2030.

The curriculum is divided into several thematic blocks: foundational AI methods; clinical and hospital data analytics; predictive modelling; medical imaging and automation; IoT‑based monitoring; EHR and NLP; public health analytics; and design of dashboards and decision‑support tools. Over 10 case studies and numerous hands‑on exercises will ensure participants not only learn theory but also apply skills to real‑world challenges.

On completion, alumni can explore roles such as AI/ML Engineer developing diagnostic models; Healthcare Data Scientist analysing clinical datasets; Clinical AI Researcher validating AI systems in hospital settings; Digital Health Consultant guiding AI adoption; Medical Imaging Analyst interpreting scans; AI Product Manager in health‑tech; or Regulatory/Data Governance Specialist ensuring compliance.

The weekend‑only format promises greater flexibility for busy professionals, with interactive live sessions and opportunities to network with CIOs, med‑tech founders and industry experts. TeamLease EdTech will support the programme delivery and student success, integrating technology platforms with IIT Delhi’s academic oversight.

Applications close on 31 July 2025. The programme will run from 1 November 2025 through early May 2026. Prospective applicants are directed to IIT Delhi’s Continuing Education Programme portal for registration and scholarship information.

This launch positions IIT Delhi and TeamLease at the forefront of AI‑driven healthcare education, anticipating a future where data intelligence plays a transformative role in patient care, system efficiency and population health outcomes.