Generative AI in Healthcare Training in Sri Lanka

This course explores how Generative AI (GenAI) is revolutionizing healthcare by enabling drug discovery, clinical decision support, personalized treatment, medical imaging enhancement, and patient engagement. It balances technical foundations, practical applications, and ethical/regulatory considerations, equipping participants with the skills to design and evaluate AI-driven healthcare solutions.

Welcome to the official Generative AI in Healthcare Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in Sri Lanka. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 14 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

• Basic understanding of AI/ML concepts.

• Familiarity with healthcare workflows (clinical, pharma, diagnostics).

• No deep programming background required, but knowledge of Python is an advantage.

• Application of AI/GenAI tools in clinical and research settings.

• Healthcare data handling and privacy-aware AI usage.

• Workflow automation for clinical documentation and patient interaction.

• Analytical and design thinking for AI-driven healthcare innovation.

• Knowledge of ethics, compliance, and bias management in healthcare AI.

By the end of the course, participants will be able to:

1. Explain how generative AI models work (LLMs, diffusion models, GANs, transformers) in a healthcare context.

2. Apply GenAI in use cases such as medical imaging, drug discovery, clinical documentation, and virtual assistants.

3. Evaluate opportunities and limitations of generative AI in healthcare delivery.

4. Address risks, ethics, and regulatory compliance (HIPAA, GDPR, FDA guidelines).

5. Design simple prototypes or workflows integrating GenAI into healthcare solutions.