Health Artificial Intelligence (AI)

Built for impact, not abstraction. Our curriculum blends theoretical and technical knowledge with real-world applications of AI in healthcare and beyond.

Core areas include:

• Foundations of AI and Machine Learning in Healthcare
• Clinical Data, EHR Systems, and Interoperability
• AI Ethics, Bias, and Regulation (FDA, HIPAA)
• Implementation Science and Change Management
• Generative AI in Healthcare
• Health System Strategy and Operations

The MS in Health Artificial Intelligence (AI) requires 33 credits. 

• AHE 502 Statistics I
• POP 500 Essentials of Population Health
• HDS 500 Fundamentals of Data Wrangling
• HAI 501 Health Informatics, Analytics, and AI
• HDS 518 Supervised Learning & Unsupervised Learning: Prediction & Classification
• HAI 527 Analytics & AI Leadership OR HDS 519 Deep Learning and AI Systems
• HAI 510 Generative AI in Healthcare
• HAI 520 10x Your Productivity with AI
• HAI 511 AI Ethics and Responsibility
• HAI 512 Databases and Data Quality
• HAI 650 Capstone

The Artificial Intelligence (AI) in Health Analytics Leadership Advanced Practice Certificate (APC) requires 15 credits. 

• HAI 501 Health Informatics, Analytics, and AI
• HDS 518 Supervised Learning & Unsupervised Learning: Prediction & Classification
• HAI 527 Analytics & AI Leadership OR HDS 519 Deep Learning and AI Systems

• Critically evaluate the machine learning algorithms that power Artificial Intelligence (AI) systems
• Integrate Artificial Intelligence (AI) into a health organization's decision-making process
• Leverage big-data assets available through electronic medical records and claims data for building Artificial Intelligence (AI) systems
• Master programming languages (e.g., Python, R, etc.) that underpin AI and Machine Learning
• Communicate key data insights and system designs to stakeholders