Johns Hopkins University Collaborates With Great Learning To Launch AI in Healthcare Program

johns-hopkins-university-collaborates-with-great-learning-to-launch-ai-in-healthcare-program

Bengaluru, December 2025.

Great Learning, a leading global edtech company, has launched theAI in Healthcare program in collaboration with Johns Hopkins University (JHU), a globally top-ranked university in medicine and public health. With a curriculum designed by Johns Hopkins University faculty, this 10-week online program equips professionals in healthcare to harness Artificial Intelligence for solving challenges, improving decision-making, and driving innovation in their field. It is ideal for medical, pharmaceutical, and biotech professionals, researchers, healthcare consultants, policymakers, and healthtech leaders, and doesn't require any programming or coding knowledge.

According to Grand View Research, the global AI in healthcare market is projected to grow at a CAGR of 38.5% till 2030, with applications ranging from diagnostics and hospital operations to drug discovery and personalised medicine. Through this collaboration, Great Learning aims to empower professionals in the healthcare industry to build systems that are data-driven, efficient, and patient-centric.

Highlighting the importance of the program, Paul Huckett, Associate Dean, Johns Hopkins Engineering Executive and Professional Education, said, “We believe the future of healthcare will be shaped by how effectively emerging technologies like AI are adopted. The AI in Healthcare program is designed not just to teach technical skills but also to cultivate leaders who can leverage AI to transform patient care, strengthen health systems, and drive innovation responsibly. Through this collaboration with Great Learning, we are creating a bridge between academic knowledge and real-world application.”

Learners begin with the basics of AI and the R.O.A.D. management framework to understand how these technologies fit into healthcare. They explore key machine-learning models, learn to measure their accuracy, and discuss ethics, regulations, and the human factors that influence adoption. The course covers predictive analytics to forecast complications, the use of large language models in healthcare, and graph analytics to study health risks and medication habits. Learners also work with epidemiological models such as Markov and SEIR to track disease spread and plan pandemic responses. Practical modules highlight common pitfalls in AI projects, best practices for managing electronic health records, and strategies for scaling pilots across hospitals.

Talking about the collaboration, Mohan Lakhamraju, Founder and CEO of Great Learning, said, "Artificial intelligence is propelling healthcare into a new era, one where care is deeply personalised, intelligent and safe. By collaborating with Johns Hopkins University, which is world‑renowned for its medicine, nursing, and public health expertise, this program ensures that learners benefit from both academic rigor and practical industry application. The program combines rigorous AI learning with healthcare-relevant applications, thus preparing professionals to not just understand AI but to apply it effectively in clinical, operational, and strategic healthcare settings."

This program offers a blend of recorded video lectures, weekly interactive mentored sessions by industry experts, and live masterclasses by JHU faculty.  They will also learn from real-world examples through 8+ practical healthcare case studies covering applications of AI in disease prediction, clinical workflows, and personalized patient care.

Learners will be awarded a Certificate of Completion and six Continuing Education Units (CEUs) from Johns Hopkins University upon successful completion of the program. As AI continues to redefine diagnostics, drug discovery, and hospital operations, this program positions professionals at the forefront of healthcare innovation, empowering them to transform challenges into opportunities and contribute to more resilient, patient-focused health systems.