AI for Healthcare Systems is a comprehensive exploration AI-relevant tools, applications and systems for mid-career healthcare and other professionals interested in this topic. This specialization benefits learners beginning to explore a career in AI for healthcare or to gain more knowledge. Systematically using analytics, reporting tools, and data visualization techniques help healthcare organizations with comprehensive insights that support better decision-making and optimizing performance. In turn, AI enhances the capabilities of healthcare professionals and systems, contributing to a more effective, efficient, and patient-centered healthcare system.
AI for Healthcare Systems Specialization
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AI for Healthcare Systems Specialization
Learn to Apply AI in Healthcare. Master strategies and tactics for broad application of AI in healthcare organizations.
Instructor: Jiban Khuntia
Included with 
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Build practical skills to design, evaluate, and apply AI solutions responsibly for healthcare’s most pressing challenges.
Harness AI and analytics to transform healthcare systems, improve decisions, and address real-world health challenges.
Develop the skills to model, design, and apply AI responsibly in advancing healthcare innovation and patient outcomes.
Overview
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
September 2025
15 practice exercises
Advance your subject-matter expertise
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Specialization - 4 course series
What you'll learn
After completing this course, you will be able to describe what AI means for healthcare and health systems.
Understand how health systems broadly use AI for the enhancement of their capabilities.
You will also develop insights into the potential of AI to solve grand healthcare challenges.
Skills you'll gain
Category: Digital Transformation
Category: Predictive Modeling
Category: Machine Learning
Category: Healthcare Industry Knowledge
Category: Responsible AI
Category: Chronic Diseases
Category: Health Systems
Category: Health Care
Category: Health Technology
Category: Health Equity
Category: Artificial Intelligence
Category: Health Informatics
What you'll learn
Understand AI’s role in the Data-Information-Analysis-Decision (DIAD) process and how it enhances decision-making in healthcare.
Analyze the integration of AI-driven analytics and machine learning algorithms in healthcare models for predictive and operational intelligence.
Assess the challenges of AI implementation in healthcare, including data governance, workflow integration, and strategic alignment.
Skills you'll gain
Category: Data-Driven Decision-Making
Category: Data Integration
Category: Digital Transformation
Category: Artificial Neural Networks
Category: Data Governance
Category: Applied Machine Learning
Category: Real Time Data
Category: Advanced Analytics
Category: Machine Learning Algorithms
Category: Business Analytics
Category: Decision Support Systems
Category: Machine Learning
Category: Health Information Management
Category: Artificial Intelligence
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Health Informatics
Category: Analytics
Category: Health Technology
Category: Predictive Analytics
What you'll learn
Understand key AI algorithms and their applications in healthcare decision-making.
Learn the fundamentals of AI modeling, including data preparation, training, and evaluation.
Explore different AI model types and design principles for effective healthcare integration.
Skills you'll gain
Category: Artificial Intelligence
Category: Exploratory Data Analysis
Category: Machine Learning
Category: Unsupervised Learning
Category: Health Informatics
Category: Decision Support Systems
Category: Data Modeling
Category: Data Mining
Category: Supervised Learning
Category: Machine Learning Algorithms
Category: Reinforcement Learning
Category: Human Factors (Security)
Category: Statistical Modeling
Category: Descriptive Analytics
Category: Applied Machine Learning
Category: Diagnostic Tests
Category: Predictive Modeling
What you'll learn
Understand the role of agentic AI and AI-driven agents in healthcare exploring their impact on automation, decision-making, and system optimization.
Apply theoretical concepts to real-world healthcare challenges, designing and executing a capstone project that addresses issues for patient care.
Develop a comprehensive AI-driven healthcare strategy.
Skills you'll gain
Category: Predictive Modeling
Category: Generative AI
Category: Generative AI Agents
Category: Artificial Intelligence
Category: AI Product Strategy
Category: Real Time Data
Category: Solution Design
Category: Data Ethics
Category: AI Personalization
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Healthcare Ethics
Category: Agentic systems
Category: Responsible AI
Category: Health Technology
Category: Health Systems
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Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
4 months with an estimated workload of 2-3 hours per week
None
It is recommended to take the courses in order
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Financial aid available,