AI+ Healthcare Foundation™ eLearning

Transform Healthcare with a Strong Foundation in AI-Driven Innovation

• Essential Healthcare AI Literacy: Build a clear understanding of how artificial intelligence is transforming diagnostics, care delivery, patient engagement, and operational workflows across modern healthcare systems.
• Safe & Responsible AI Use: Learn foundational principles for evaluating AI tools, ensuring accuracy, minimizing risks, upholding patient safety, and supporting ethical, compliant decision-making in clinical environments.
• Data Foundations for Healthcare: Gain practical insight into healthcare data types, EHR systems, and the role of structured, high-quality clinical data in powering reliable AI applications.
• AI in Public Health & Care Continuity: Explore how AI improves population health management, early detection, disease surveillance, and care coordination, strengthening outcomes across diverse patient communities.
• Preparing for the Future of Care: Develop the knowledge needed to collaborate with clinicians and technologists, navigate emerging AI trends, and adapt confidently to the evolving digital healthcare landscape.

Module 1: Introduction to Artificial Intelligence (AI)

• 1.1 Fundamentals of Artificial Intelligence
• 1.2 AI in the Healthcare Ecosystem
• 1.3 Case Study: Mayo Clinic’s Digital Transformation
• 1.4 Case Study: UnitedHealthcare’s Predictive Analytics
• 1.5 Case Study: Pfizer and COVID-19 Vaccine Development
• 1.6 Case Study: ACO Models in the U.S.

Module 2: Introduction to Prompt Engineering

• 2.1 Introduction to Principles of Effective Prompting
• 2.2 Giving Direction
• 2.3 Formatting Responses
• 2.4 Applying the Five Principles

Module 3: Data Handling and AI Modelling in Healthcare

• 3.1 Understanding Clinical Data Types—EHRs, Vitals, Lab Results
• 3.2 Structured vs. Unstructured Data in Medicine
• 3.3 Interactive Activity: AI Assistant for Clinical Note Insights

Module 4: Ethical, Legal and Societal Considerations

• 4.1 Introduction to AI Ethics and Social Implications
• 4.2 Bias and Fairness in AI
• 4.3 Privacy and Security in the Age of AI
• 4.4 Responsible AI Development
• 4.5 AI and Society: Looking Ahead

Module 5: AI Applications in Healthcare

• 5.1 Innovations in AI and Their Impact on Healthcare
• 5.2 Interdisciplinary Approaches
• 5.3 Preparing for the Future

Tools you will explore

• TensorFlow
• Keras
• Python
• Healthcare Data Analytics Tools
• Natural Language Processing (NLP) for Medical Text
• SQL
• Power BI
• Healthcare System Integration Platforms
• Machine Learning Algorithms for Healthcare
• Electronic Health Record (EHR) Integration Tools
• Predictive Analytics Platforms
• AI-Powered Decision Support Systems
• Medical Imaging AI Tools

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Self study materials are available for 365 days.

Instructor-led OR Self-paced course + Official exam + Digital badge