Overview

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Build the conceptual foundation you need to support healthcare AI initiatives. This course introduces how Healthcare AI Coordinators, Clinical AI Project Coordinators, and Healthcare AI Implementation Analysts bridge clinical, business, project, and technical teams; how organizational priorities shape AI strategy; and how core health informatics concepts apply to AI implementation work. You'll explore the Healthcare AI Program Manager role across provider, research, consulting, payer, and pharmaceutical settings; organize executive inputs into a draft healthcare AI strategy brief and rollout outline; and apply health informatics terminology to interpret real project artifacts such as data dictionaries, workflow notes, and system diagrams. No prior AI or healthcare technology experience required—all concepts are introduced from the ground up. This course is suitable for learners who want a portfolio artifact demonstrating foundational skills.

Syllabus

Healthcare AI PM Role: Role Responsibilities Across Provider Settings
- Meet the Healthcare AI Program Manager role as it actually exists in provider organizations, and see how the same title looks different in a 500-bed hospital versus a five-provider clinic versus a multi-site health system. You'll be able to describe entry-level PM responsibilities in provider settings with confidence.
Healthcare AI PM Role: Analyze Scope Factors
- Learn why the same job posting can mean very different work depending on where you land, and pick up a simple three-factor rubric for reading a healthcare AI initiative to figure out what an entry-level PM would support, document, or escalate.
Healthcare AI Strategy: Describe Strategy Components
- Learn what actually goes into a healthcare AI strategy at the component level—and how to spot a well-scoped versus under-scoped strategy component when you read one.
Healthcare AI Strategy: Draft Brief and Rollout Outline
- Turn messy executive inputs, emails, meeting notes, and verbal directives into a structured draft strategy brief and rollout outline that a senior lead can pick up and act on. Use the strategy brief template, populate it with traceable inputs, and produce a high-level rollout outline that progresses from executive approval through pilot to organizational adoption.
Health Informatics: Core Concepts for AI Projects
- This module builds the informatics literacy that turns opaque project artifacts into readable ones. It explains three foundational areas—clinical data types, workflow context, and system-to-process relationships—and applies them as a lens for interpreting healthcare AI project artifacts.
Health Informatics: Interpret Project Artifacts
- This module applies informatics terminology to interpret real project artifacts. It works through a mixed artifact packet—data dictionary, workflow notes, and system diagram—to produce a clean interpretation memo that a senior lead can use in stakeholder conversations.
Project Module: Draft a Healthcare AI Initiative Briefing
- Bring together everything from LC 1 to produce an entry-level portfolio artifact, a healthcare AI initiative briefing that a Senior AI Program Manager could pick up and refine for an executive presentation. You'll organize discovery inputs into a structured strategy brief, add an informatics interpretation of the initiative's data landscape, and outline a realistic rollout, all scoped to what an entry-level Healthcare AI Coordinator would perform.

Taught by

Microsoft

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