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
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
(7 reviews)
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
(7 reviews)
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
Skills you'll gain
- Data Governance
- Health Information Management
- Artificial Intelligence
- Information Systems
- Analytics
- Health Systems
- Digital Transformation
- Healthcare Industry Knowledge
- Machine Learning Algorithms
- Agentic systems
- Generative AI Agents
- Health Informatics
- Artificial Intelligence and Machine Learning (AI/ML)
- Information Technology
- Machine Learning
- Health Technology
- Healthcare Ethics
- Responsible AI
- Human Factors (Security)
- Data Ethics
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
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from University of Colorado System
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
Artificial Intelligence, Chronic Diseases, Predictive Modeling, Machine Learning, Health Informatics, Responsible AI, Health Care, Health Technology, Healthcare Industry Knowledge, Digital Transformation, Health Equity, and Health Systems
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
Artificial Intelligence, Data-Driven Decision-Making, Machine Learning Algorithms, Analytics, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Digital Transformation, Predictive Analytics, Health Technology, Data Integration, Advanced Analytics, Data Governance, Decision Support Systems, Business Analytics, Applied Machine Learning, Health Information Management, Real Time Data, Artificial Neural Networks, and Health Informatics
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
Machine Learning, Predictive Modeling, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Diagnostic Tests, Descriptive Analytics, Exploratory Data Analysis, Applied Machine Learning, Reinforcement Learning, Statistical Modeling, Data Mining, Decision Support Systems, Health Informatics, Data Modeling, Human Factors (Security), and Machine Learning Algorithms
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
Artificial Intelligence, Agentic systems, Solution Design, Responsible AI, Healthcare Ethics, Generative AI, Data Ethics, Predictive Modeling, AI Product Strategy, Health Systems, AI Personalization, Real Time Data, Health Technology, Generative AI Agents, and Artificial Intelligence and Machine Learning (AI/ML)
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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,