Skills you will learn

  • AI Fundamentals
  • Generative AI Basics
  • Healthcare Data Analysis
  • Clinical AI Applications
  • Medical Imaging
  • Decision Support Systems
  • Workflow Automation
  • Responsible AI
  • Data Privacy
  • Bias Detection

Who should learn

  • Healthcare Professionals
  • Medical Students
  • Hospital Administrators
  • Medical Data Analysts
  • Operations Managers
  • Public Health Officials

What you will learn

  • Free Course: AI for Healthcare Clinical Insights

    • Lesson 01: Course Introduction

      05:40
      • 1.01 Trainer Introduction
        02:58
      • 1.02 Course Introduction
        02:42

    • Lesson 02: Introduction to AI and Gen AI in Healthcare

      31:58
      • 2.01 Learning Objectives
        01:14
      • 2.02 AI in Healthcare Overview and Use Cases
        03:04
      • 2.03 GenAI in Healthcare and Its Benefits
        04:03
      • 2.04 Types of AI Applications in Healthcare
        05:52
      • 2.05 Overview of Healthcare Data
        01:48
      • 2.06 Why AI and Generative AI are Essential for Modern Healthcare
        04:44
      • 2.07 Case Study DeepMind AI for Breast Cancer Screening
        03:07
      • 2.08 Demo Analyzing EHR Risk Patterns Using ChatGPT
        07:14
      • 2.09 Key Takeaways
        00:52

    • Lesson 03: AI for Clinical Applications

      01:04:58
      • 3.01 Learning Objectives
        01:21
      • 3.02 Introduction to Clinical Care and the Role of AI
        02:08
      • 3.03 Overview of Clinical AI Applications
        04:05
      • 3.04 Evaluation of Clinical AI Applications
        01:03
      • 3.05 AI in Medical Imaging
        00:46
      • 3.06 AI in Radiology Workflow Clinical Utility and Key Use Cases
        04:18
      • 3.07 AI in Pathology Workflow Clinical Utility and Key Use Cases
        03:03
      • 3.08 Demo Summarizing Clinical Notes with ChatGPT Part 1
        09:23
      • 3.09 Demo Summarizing Clinical Notes with ChatGPT Part 2
        06:35
      • 3.10 Clinical Decision Support Systems Components and Functionality
        02:53
      • 3.11 How AI Assists Doctors in Decision Making
        03:24
      • 3.12 AI Assisted vs Traditional Clinical Decision Making
        01:39
      • 3.13 AI Based Patient Risk Prediction and Early Disease Detection
        01:14
      • 3.14 How AI Based Predictive Models Function in Practice
        00:58
      • 3.15 Clinical Scenarios with High Impact of AI Based Prediction
        01:26
      • 3.16 Case Study Mayo Clinics AI System for Early Detection of Heart Failure
        03:22
      • 3.17 AI Powered Treatment Personalization Clinical Use Cases
        04:54
      • 3.18 AI in Precision Medicine Concepts and Clinical Impact
        06:33
      • 3.19 AI in Drug Discovery and Genomics
        03:23
      • 3.20 Key Takeaways
        02:30

    • Lesson 04: AI in Healthcare Operations

      01:27:50
      • 4.01 Learning objectives
        01:59
      • 4.02 Introduction to Healthcare Operations
        03:31
      • 4.03 Overview of Operational Challenges in Healthcare
        03:23
      • 4.04 Impact of Operational Challenges
        02:05
      • 4.05 How AI Mitigates Healthcare Operational Challenges
        03:52
      • 4.06 Introduction to Hospital Administrative Workflows
        03:56
      • 4.07 Challenges in Hospital Administrative Workflows
        03:22
      • 4.08 How AI Improves Administrative Workflows
        02:26
      • 4.09 Hospital Operational Workflow Overview and Key Bottlenecks
        03:05
      • 4.10 Applying AI to Hospital Workflow Automation
        03:09
      • 4.11 Optimizing Patient Scheduling with AI
        05:37
      • 4.12 Optimizing Hospital Resource Management with AI
        05:34
      • 4.13 Remote Patient Monitoring Workflow AI and Roles
        06:56
      • 4.14 Demo Streamlining Appointment Scheduling and Reducing Wait Times with AI Part 1
        07:42
      • 4.15 Demo Streamlining Appointment Scheduling and Reducing Wait Times with AI Part 2
        08:45
      • 4.16 Understanding Healthcare Billing and Insurance Challenges
        04:42
      • 4.17 Applying AI Across Healthcare Billing Operations
        03:47
      • 4.18 Demo Using the Buoy AI Health Assistant for Symptom Checking
        12:15
      • 4.19 Key Takeaways
        01:44

    • Lesson 05: AI for Public Health: Predicting Risks

      28:55
      • 5.01 Learning Objectives
        00:52
      • 5.02 Introduction to Public Health and Data Collection
        03:29
      • 5.03 Public Health Data Collection and Community Analytics
        03:19
      • 5.04 Smart City and Healthcare Data Integration
        01:09
      • 5.05 Disease Trend Forecasting Using AI
        02:51
      • 5.06 AI Platforms Used in Public Health Surveillance
        00:56
      • 5.07 AI-Powered Public Health Surveillance and Decision Making
        00:55
      • 5.08 Case Study BlueDot AI Detected COVID 19 Outbreak Before Global Alerts
        02:05
      • 5.09 Demo Using Microsoft Copilot for Community Risk Assessment and Action Planning
        12:24
      • 5.10 Key Takeaways
        00:55

    • Lesson 06: Responsible AI, Governance and Future of AI in Healthcare

      59:36
      • 6.01 Learning Objectives
        03:20
      • 6.02 Introduction to Responsible AI in healthcare
        06:56
      • 6.03 Understanding AI Risks and Ethical Principles
        06:17
      • 6.04 Data Confidentiality in Healthcare AI
        03:38
      • 6.05 Protecting Patient Information and Managing AI Privacy Risks
        07:00
      • 6.06 Demo Identifying Protected Health Information in a Healthcare Dataset Using Microsoft Copilot
        13:20
      • 6.07 Understanding Bias and AI Governance in Healthcare
        05:15
      • 6.08 Healthcare AI Regulatory Considerations
        04:01
      • 6.09 Responsible AI Safeguards in Healthcare
        02:04
      • 6.10 Responsible AI Safeguards in Healthcare Privacy Safeguards and Bias Safeguards
        02:13
      • 6.11 Responsible AI Safeguards in Healthcare Governance Safeguards and Compliance Safeguards
        04:38
      • 6.12 Key Takeaways
        00:54
About the Course

If you work in healthcare, you know the challenges: heavy workloads, complex patient data, and the difficulty of keeping operations running smoothly. This course will show you how AI can help with these issues. You’ll learn to use AI to support clinical care, make healthcare processes better, and improve public health efforts.

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FAQs

  • What does this course cover?

    This course covers AI in clinical care – how it helps with diagnosis and treatment – healthcare operations like scheduling and billing, and public health applications like disease prediction. You’ll also learn how to use AI responsibly and handle privacy and regulatory concerns.

  • Do I need a healthcare background to take this course?

    Not at all. The course explains healthcare concepts as we go, so you don’t need prior experience. If you already work in healthcare, you’ll see how it applies to your work. If you’re new to the field but interested in AI, you’ll learn plenty.

  • Is this course technical or non-technical?

    We’ve designed it for everyone. You don’t need to know how to code, but you should be comfortable learning about data and technology. We explain things in plain language and show you demos with tools you can actually use.

  • What are the main topics covered in this course?

    • How AI and generative AI work: the real mechanics

    • AI in clinical care, imaging, diagnosis, and treatment

    • AI in healthcare operations and administration

    • Public health surveillance and disease prediction

    • Responsible AI, privacy, bias, and governance

    • Real case studies and working demos you can learn from

  • Will I learn about specific healthcare AI tools?

    • ChatGPT and Microsoft Copilot for healthcare work

    • Real hospital AI systems and what they actually do

    • Public health AI platforms in use today

    • Tools for analyzing healthcare data the right way

  • How does this course handle patient privacy?

    You’ll learn how to spot protected health information, anonymize data properly, understand laws like HIPAA, and build AI systems that actually protect patient information.

  • Can I use what I learn if I work in a small clinic or practice?

    Absolutely. Small clinics sometimes benefit even more from AI than large hospitals. The principles we teach work everywhere from solo practices to huge hospital networks.

  • Do I need coding skills to complete this course?

    No. We use tools like ChatGPT and Copilot for the demos, and they don’t require you to write code. Anyone comfortable with regular software can follow along.

  • How long does it take to complete this course?

    The course has 6 lessons, each with multiple video segments. You move at your own pace, but most people spend 8 to 15 hours total depending on how much time they spend with the demos.

  • Will this course prepare me for healthcare AI certifications?

    This gives you a solid foundation in AI in healthcare. It’s a perfect stepping stone if you want to get specialized certifications in healthcare informatics or clinical data science later.

  • How current is the information about AI tools and applications?

    The course reflects the current state of AI in healthcare. But here’s the thing - healthcare AI moves fast. We recommend staying updated on new tools and applications after you finish.

  • Will I understand healthcare regulations around AI?

    Yes, Lesson 6 covers all that. You’ll learn about HIPAA, FDA regulations for AI in healthcare, and data governance requirements so you know what you need to follow.

  • Can I apply this to my own healthcare organization?

    This course offers practical frameworks to help you evaluate and adopt AI effectively. You’ll learn how to begin with small steps, track outcomes, and scale AI solutions responsibly.

  • Will I get a certificate after completing this course?

    Yes, you’ll get a certificate showing you’ve completed comprehensive training in AI in healthcare. It’s perfect for your LinkedIn profile or resume to show employers you know this stuff.

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