AI+ Healthcare Foundation (AP 4800 Self-Paced Training)

  • 1 Tag
  • Einsteiger
  • Englisch
  • 168 € zzgl. MwSt.
  • Bescheinigung und digitales Badge
Kurs anfragen

Worum es geht

The AI+ Healthcare Foundation™ certification is designed to provide foundational healthcare AI literacy, equipping learners with a clear understanding of how artificial intelligence transforms diagnostics, patient care delivery, operational workflows, and population health management. It focuses on safe and responsible AI use, practical insight into healthcare data and systems, and preparing participants to collaborate with clinicians and technologists while navigating emerging AI trends in healthcare. Learners will also engage with “What Will You Learn?” outcomes including AI fundamentals for healthcare, data analysis and insights, healthcare system integration with AI, predictive patient monitoring, and ethics and privacy in healthcare AI.

Für wen

  • Healthcare Professionals seeking to understand AI’s impact on patient care and efficiency.
  • Data Analysts interested in applying data analytics and AI in healthcare contexts.
  • Tech Enthusiasts with an interest in AI and machine learning’s role in healthcare innovation.
  • Medical Researchers exploring AI in clinical data analysis.
  • Aspiring AI Engineers aiming to work with data-driven healthcare solutions.

Inhalte

Module 1: Introduction to Artificial Intelligence (AI)
  • 1.1 Fundamentals of Artificial Intelligence
  • 1.2 AI in the Healthcare Ecosystem
  • 1.3 Case Study: Mayo Clinic’s Digital Transformation
  • 1.4 Case Study: UnitedHealthcare’s Predictive Analytics
  • 1.5 Case Study: Pfizer and COVID-19 Vaccine Development
  • 1.6 Case Study: ACO Models in the U.S.
Module 2: Introduction to Prompt Engineering
  • 2.1 Introduction to Principles of Effective Prompting
  • 2.2 Giving Direction
  • 2.3 Formatting Responses
  • 2.4 Applying the Five Principles
Module 3: Data Handling and AI Modelling in Healthcare
  • 3.1 Understanding Clinical Data Types—EHRs, Vitals, Lab Results
  • 3.2 Structured vs. Unstructured Data in Medicine
  • 3.3 Interactive Activity: AI Assistant for Clinical Note Insights
Module 4: Ethical, Legal and Societal Considerations
  • 4.1 Introduction to AI Ethics and Social Implications
  • 4.2 Bias and Fairness in AI
  • 4.3 Privacy and Security in the Age of AI
  • 4.4 Responsible AI Development
  • 4.5 AI and Society: Looking Ahead
Module 5: AI Applications in Healthcare
  • 5.1 Innovations in AI and Their Impact on Healthcare
  • 5.2 Interdisciplinary Approaches
  • 5.3 Preparing for the Future

Voraussetzungen

  • Foundational understanding of healthcare systems and terminology.
  • Data analytics skills for interpreting healthcare information.
  • Awareness of AI concepts and machine learning fundamentals.
  • Basic programming knowledge (e.g., Python).
  • Critical thinking/problem-solving abilities for healthcare challenges.

Zertifizierung

  • 50 Multiple-Choice Questions (MCQs)
  • 90-minute duration
  • Passing Score: 70% (35/50)
  • Modules Count: 5 + Examination (1)

Im Preis enthalten

  • Offizielle Hersteller-Unterlage (digital, engl. Sprache)
  • Offizielle Schulungsumgebung (LAB)
  • Prüfungsvoucher
  • Teilnahmebescheinigung und digitales Badge

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