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OPEN ENROLLMENT PROGRAM
Health Care Transformation
Dates: November 21, 2024 – April 3, 2025
Last Day to Enroll: November 21, 2024
Duration: 18 weeks
Format: Online and Live Virtual
Fee: $4,995
AI in Health Care: From Strategies to Implementation
Leading Digital Transformation in Health Care
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Part 1 — AI in Health Care: From Strategies to Implementation
- Module 1: The History and Foundations of AI
- Module 2: A Framework for the AI Development Pipeline
- Module 3: From the Lab to the Real World
- Module 4: Transparency, Reproducibility, and Generalizability in AI
- Module 5: The Potential for Bias and Harm in AI
- Module 6: AI for Startups
- Module 7: AI for Wearable Data
- Module 8: Live Session — Capstone Presentations
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Part 2 — Leading Digital Transformation in Health Care
- Module 1: Transforming, Disrupting, or Staying Competitive
- Module 2: Enabling Technologies
- Module 3: Transformation Management Skills and Practices — Fostering Change Management
- Module 4: Transformation Management Skills and Practices — Establishing Digital Transformation and Innovation
- Module 5: Transformation Management Skills and Practices — Creating a Digital Culture
- Module 6: Creating the Transformation Plan
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Part 3 — Exclusive Learning Modules
- Module 0: Program Orientation
Explore the program's objectives and expected learning outcomes, and gain an overview of the health care industry, focusing on the transformative role of AI and digital technologies. - Module 1: Management Education
Delve into the fundamental concepts of management education in health care, and discuss various leadership styles and effective management practices. - Module 2: Organizational Learning
Discover strategies for fostering a learning organization within the health care sector, emphasizing the importance of continuous professional development, and describing the potential business value for AI pilots. - Module 3: Innovation Management
Examine the process of innovation in health care, and gain tools and techniques for managing innovation effectively by proposing an approach for integrating an AI innovation group. - Module 4: Framework Analysis 1
Analyze techniques for evaluating AI implementation frameworks and their applicability in health care. Analyze the elements of a peer's framework for implementing AI, and integrate peer feedback. - Module 5: Dealing with Vendors
Delve into best practices for selecting and managing AI vendors, including critical considerations for vendor evaluation and relationship management. Describe diligence activities associated with examining an AI-based product or service. - Module 6: Managing AI Limitations and Potential Problems
Identify and manage potential challenges in AI implementation, and develop strategies for mitigating risks and addressing limitations. - Module 7: Framework Analysis 2
Refine AI implementation frameworks, incorporating feedback to enhance framework effectiveness. Analyze the elements of a peer's framework for implementing AI, and integrate peer feedback. - Module 8: Mid-Program Summary
Discuss the application of AI insights in real-world health care settings, and reflect on the learnings gained in approaching AI solutions in health care. - Module 9: Strategic Context
Set the strategic context for AI in health care by aligning AI initiatives with organizational strategy. Defend the AI strategic context selected for an organization. - Module 10: Governance
Explore governance frameworks for AI implementation, and outline a charter for an AI governance committee. - Module 11: Talent Management
Examine the potential impact of AI on organizational talent management in health care, and describe the potential impact of AI on an organization's talent needs. - Module 12: Data Management
Delve into best practices for managing data in AI projects by analyzing data management practices to ensure data quality, security, and compliance. - Module 13: Technology Architecture
Assess the impact of AI on technology architecture, and describe methods used to assess the impact of an AI-based application on an organization’s infrastructure. - Module 14: Framework Analysis 3
Discover advanced techniques for framework analysis, enhancing the effectiveness of AI implementation frameworks. Analyze the elements of a peer's framework for implementing AI, and integrate that feedback into your framework. - Module 15: Implementation Issues
Compare successful and unsuccessful AI implementation projects, and learn from failures and best practices. - Module 16: Industry Participation
Explore and discuss the importance of participating in AI-centered industry forums and communities. - Module 17: Framework Analysis 4
Finalize and refine AI implementation frameworks, preparing them for real-world application. Analyze the elements of a peer's framework for implementing AI, and integrate that feedback into your framework. - Module 18: Program Wrap-Up
Summarize program learnings, and engage in final discussions while exploring future directions in AI for health care. Develop a comprehensive framework for implementing AI.
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