Learn more about the course
Get details on syllabus, projects, tools, and more
Upskill Your Teams with Future-Ready Skills
Empower your workforce with programs from leading universities
-
Team Pricing
Maximize ROI with exclusive cost-effective plans for group enrollments
-
Team Learning Dashboard
Track progress & outcomes at the team level
-
Customized Learning Paths
Tailor the program to align with your team's goals and drive meaningful outcomes.
Enter your organisation name
This will help us customise the proposal plans
AI in Healthcare Program
Application closes 18th Jun 2026
Why should you join this program?
-
Healthcare-Focused AI Curriculum
Learn from Johns Hopkins University faculty and industry experts to build expertise in applying AI to improve patient outcomes and healthcare delivery through real-world case studies.
-
Learn from a Global Leader in Medical Research and Healthcare
Ranked #1 in Biomedical Engineering, #7 National University, #2 in Computer Information Technology, JHU is a leader in healthcare research and innovation. (2026 Rankings)
PROGRAM OUTCOMES
What will you learn to build and apply?
Through a structured learning journey, you will build the capability to:
-
AI Fundamentals and Integration: Gain insights into AI technologies and the R.O.A.D. Management framework
-
Machine Learning: Differentiate six key algorithms and evaluate them using metrics like accuracy & F1 score.
-
Human Baseline & Ethics: Analyze psychosocial predictors, ethical challenges, AI regulations in healthcare.
-
Predictive Analytics: Understand AI in forecasting complications and handling data overload, including LLMs.
Earn a Certificate from Johns Hopkins University
KEY PROGRAM HIGHLIGHTS
Why choose the AI in Healthcare Program
-
Learn from JHU Faculty
Learn through recorded lectures and attend faculty-led masterclasses covering AI project management, healthcare AI trends, and AI-powered clinical risk assessment.
-
Interactive Mentorship by Industry Experts
Learn from healthcare AI practitioners through mentored sessions focused on practical applications, implementation challenges, and industry best practices.
-
Healthcare-Focused AI Curriculum
Build expertise in clinical decision support, predictive analytics, population health, healthcare AI strategy, and responsible AI.
-
Real-World Healthcare Case Studies
Analyze 8+ healthcare case studies covering disease prediction, clinical decision support, AI adoption, healthcare ethics, and patient care.
-
Earn a Recognized Credential from JHU
Earn a Certificate of Completion and 6 CEUs from Johns Hopkins University upon successful completion of the program.
-
Personalized Program Support
Receive 1:1 guidance from a dedicated Program Manager and academic support from subject matter experts.
Skills you will learn
Applying AI Solutions in Healthcare
Predictive Analytics for Disease Management
Ethical AI Practices and Regulatory Compliance
AI-Driven Decision Support Systems
AI Project Management for Healthcare Initiatives
Large Language Models (LLMs) in Healthcare
Strategic AI Integration in Healthcare Systems
Machine Learning Algorithms for Clinical Applications
Robotic Process Automation in Clinical Settings
Change Management for AI Adoption in Hospitals
Applying AI Solutions in Healthcare
Predictive Analytics for Disease Management
Ethical AI Practices and Regulatory Compliance
AI-Driven Decision Support Systems
AI Project Management for Healthcare Initiatives
Large Language Models (LLMs) in Healthcare
Strategic AI Integration in Healthcare Systems
Machine Learning Algorithms for Clinical Applications
Robotic Process Automation in Clinical Settings
Change Management for AI Adoption in Hospitals
view more
- Overview
- Learning Journey
- Curriculum
- Projects
- Certificate
- Faculty
- Mentors
- Reviews
- Fees
Who is the program for?
Professionals Seeking to Harness AI in Healthcare
-
Technical Professionals and Healthcare Consultants
Master AI techniques to analyze healthcare data, automate routine tasks, and enhance clinical decision-making.
-
Business and Strategy Leaders in Healthcare
Lead AI-driven healthcare initiatives, optimize operational efficiency, and drive strategic business outcomes.
-
Medical, Pharmaceutical and Biotech Professionals
Apply AI to enhance diagnostics, personalize treatment plans, and accelerate medical research.
-
Regulators and Healthcare Policymakers
Leverage AI for policy analysis, data-driven decision-making, and effective resource allocation in public health.
How is the program learning experience?
Through a structured learning approach, develop the strategic judgment and intuition to scale AI
-
Learn from Experts
Learn from JHU faculty and industry experts to build AI powered healthcare solutions
-
Learn By Doing
Apply AI concepts through case studies focused on patient outcomes and healthcare innovation
-
Earn a University Credential
Earn a certificate of completion and 6 CEUs from Johns Hopkins University
-
Get Support Throughout the Learning Journey
Program managers will help you stay on track, navigate key milestones & complete the program
What will you learn in the program?
Designed by the renowned Johns Hopkins University faculty, the AI in Healthcare program covers foundational AI concepts, clinical decision support, health and disease management, business strategy, plus 3 masterclasses on AI project implementation, future industry trends, and workflow automation. It requires no prior programming experience.
Pre-Work: Introduction to the World of AI in Healthcare
Gain foundational knowledge on AI's evolution in healthcare, including key milestones, ethical considerations, and real-world impact.
Module 1: Foundations of AI for Healthcare
In this module, you will learn the fundamentals of Artificial Intelligence (AI) and its core technologies, focusing on their application in healthcare. You will explore the R.O.A.D. Management Framework for AI integration, define algorithms, and differentiate key machine learning models. Additionally, you will evaluate model performance using metrics like accuracy and F1 score, and assess the difference between pseudo-innovation and real innovation in healthcare.
Week 1: AI in Healthcare: Foundations and Frameworks
Week 2: Understanding the Building Blocks of AI in Healthcare
Module 2: AI for Intelligent Decision Support
This week, you will explore how AI has the potential to enhance decision-making in healthcare by leveraging predictive modeling, neural networks, and deep learning. You will analyze the concept of human baseline in AI, risk-based approaches, and psychological factors, including prospect theory and status quo bias. The module also covers AI's role in managing information overload, the potential of Large Language Models (LLMs) in improving healthcare workflows, and the challenges associated with AI biases and human oversight.
Week 3: AI for Clinical Decision Support
Week 4: Large Language Model Fundamentals and Clinical Considerations
Week 5: Automation/Robotics for Healthcare
Module 3: AI for Population Health & Disease Management
Upon completing this module, you will be able to analyze graph analytics related to co-morbidity, identifying risk factors and social influences on health interactions to improve patient management. You will explore the cultural impacts on medication adherence and their implications for public health interventions. Further, in the module, you will apply frameworks like Markov models and SEIR to assess disease spread for improving health outcomes during pandemics to assess disease spread and the effectiveness of AI tools during pandemics. Additionally, you will examine AI's role in precision medicine to enhance health screening, treatment protocols, and early disease detection, optimizing preventive healthcare strategies, and improving patient outcomes.
Week 6: AI for Improved Health Outcomes
Week 7: Learning Break
Week 8: Designing Preventive Healthcare Strategies
Module 4: AI Business Strategy for Healthcare
Upon completion of this module, you will understand the R.O.A.D. Management Framework for AI integration in healthcare and identify common pitfalls in AI projects, proposing risk mitigation strategies. You will analyze ethical, regulatory, and privacy challenges, along with best practices for managing datasets in Electronic Health Records (EHRs). You will assess healthcare leadership styles and their impact on AI adoption, explore social network strategies for organizational change, and evaluate methods for scaling AI pilot projects to full hospital implementation. Lastly, you will investigate career paths in AI within healthcare, identify essential skills, and understand AI's role in optimizing pharmaceuticals and medical devices to enhance efficacy and patient safety.
Week 9: Health Data & Ethics
Week 10: Change Management & Adoption
Self-Paced Module | Claude-Based AI Workflows
This module is designed to build practical capability in applying Generative AI and Agentic AI using the Claude ecosystem in real-world contexts. Participants build the ability to design, execute, and evaluate AI-driven workflows for real-world applications, supported by ~5 hours of structured learning.
Design and Execute AI Workflows
Build and Deploy AI Systems at Scale
Masterclass 1: AI Project Management & Design
This Masterclass focuses on the R.O.A.D. Management Framework for integrating AI in healthcare and exploring key components essential for successful implementation. The session covers strategic AI integration, common pitfalls in AI projects, and the impact of data issues on AI success. Learners will examine the role of stakeholder engagement, the influence of change management, and factors that contribute to successful AI project outcomes. Additionally, the masterclass will provide mitigation strategies to address risks and challenges, increasing the probability of the effective deployment of AI-driven solutions in healthcare.
Masterclass 2: Future Trends in AI & Healthcare
This masterclass will help you explore career paths in AI within the healthcare sector by developing the skills and competencies required for success. The session will cover strategies for personal career advancement and the growing role of AI in pharmaceuticals and medical devices. Learners will assess how AI has the potential to enhance efficacy, reduce time-to-market for new treatments, and improve patient safety. Additionally, the masterclass will teach the specific skills to determine whether AI-driven solutions truly optimize medical devices and provide greater precision and reliability in healthcare applications.
Masterclass 3: AI-Powered Pre-Visit Clinical Risk Assessment Using N8N
In this masterclass, you will understand how AI can streamline pre-visit clinical workflows by organizing unstructured patient data, identifying early risk patterns, and improving clinical efficiency. The session covers the challenges of fragmented clinical data, fundamentals of AI-driven pre-visit risk assessment, and core principles such as structured data, visibility, and decision support. Participants will also explore workflow automation using no-code tools like n8n, including an end-to-end patient intake to pre-visit summary pipeline. Additionally, the masterclass examines NLP and AI techniques for clinical data organization, rule-based risk detection, and patient prioritization. It will also highlight the impact of AI-powered pre-visit assessments on patient safety, operational efficiency, and future healthcare innovations, while emphasizing how intelligent workflows can support clinician decision-making.
What case studies will you solve?
Work on healthcare AI case studies covering disease prediction, diagnostics, and patient care
Earn a Professional Certificate from Johns Hopkins University
Stand out in a competitive market with a Certificate of Completion in AI in Healthcare that formally recognizes the expertise developed through rigorous, practical assessments.
-
Biomedical Leadership
#1 Biomedical Engineering Program by U.S. News & World Report, 2026
-
National Recognition
#7 National University by U.S. News & World Report, 2026
-
Global Standing
#14 Best Global University by U.S. News & World Report, 2026
* Image for illustration only. Certificate subject to change.
Who are the faculty for the program?
Learn from renowned JHU faculty and build the expertise to evaluate and implement AI in healthcare settings.
Who are the mentors for weekly live sessions?
Learn from seasoned AI healthcare mentors to apply concepts and build practical skills.
Course Fees
The program fee is USD 2,990
Lead AI Innovation in Healthcare
-
Build expertise in applying AI to clinical decision support and predictive analytics for better patient care.
-
Dedicate 6–8 hours weekly to faculty-led learning, industry mentorship, and healthcare case studies
-
Learn from healthcare AI practitioners through live online sessions focused on industry applications.
-
Receive a Certificate of Completion and 6 CEUs from Johns Hopkins University.
-
INSTALLMENT PLANS
Upto 12 months Installment plans
Explore our flexible payment plans
View Plans
Third Party Credit Facilitators
Check out different payment options with third party credit facility providers
*Subject to third party credit facility provider approval based on applicable regions & eligibility
Admission Process
Admissions close once the required number of participants enroll. Apply early to secure your spot
-
1. APPLY
Fill out an online application form.
-
2. REVIEW
Your application will be reviewed by a panel from Great Learning to determine if it is a fit with the program
-
3. JOIN PROGRAM
After a final review, you will receive an offer for a seat in the upcoming cohort of the program.
Batch start date
-
Online · To be announced
Admissions Open
Delivered in Collaboration with:
Johns Hopkins University is collaborating with online education provider Great Learning to offer the AI in Healthcare Program. Great Learning is a professional learning company with a global footprint in 14+ countries. Its mission is to make professionals around the globe proficient and future-ready. This program leverages JHU's leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great Learning manages the enrollments and provides industry experts, student counselors, course support and guidance to ensure students get live personalized mentorship on the application of concepts taught by the JHU faculty.