Course curriculum

    1. AI Usage in Healthcare

    2. Introduction

    3. Overview

    4. Examples of AI in Healthcare

    5. Examples of AI in Healthcare Cont.

    1. Introduction

    2. Overview

    3. Machine Learning Review

    4. Identifying a Classification Scenario

    5. Microsoft Azure

    6. Steps for Classification

    7. Classification Real World Examples

    8. Classification Demonstration Introduction

    9. Enabling Resource Providers: PolicyInsights / Cdn

    10. ML Service Creation

    11. Navigate to ML Studio

    12. ML Studio Tour

    13. Computing Instance

    14. Upload Dataset

    15. Create Dataset

    16. Dataset Analysis

    17. Select Columns

    18. Normalization

    19. Split Data

    20. Train Model

    21. Submitting Job

    22. Reviewing Performance

    23. Creating Inference Pipeline

    24. Entering Manual Data

    25. Submitting Inference Pipeline

    26. Initiating Real-time Endpoint

    27. Deploying Model

    28. Testing on New Unseen Data

    29. Congratulations on Completing This Module!

    1. Introduction to NLP in Healthcare

    2. Overview

    3. Language Service / Studio

    4. Extract Healthcare Model

    5. AI in Healthcare Examples

    6. Healthcare Demonstration Introduction

    7. Language Service Creation

    8. Language Studio Navigation

    9. Testing Azure's Pre-trained Model

    1. Types of Computer Vision

    2. Microsoft Azure

    3. Optical Character Recognition

    4. OCR and Text Analysis

    5. OCR and Translation

    6. AI in Healthcare Scenario

    7. Microsoft Azure Resource Creation

    8. OCR in Healthcare

    1. Introduction

    2. Early Detection of Strokes

    3. Radiogenomics

    4. Diabetes Care

    5. Baricitinib

    6. Congratulations on completing this course!

About this course

  • $850.00
  • 5 Modules
  • 15 hours of learning content

Course Highlights

  • Develop AI-powered healthcare solutions using real-world data

  • Gain hands-on experience with tools like Azure AI, NLP, and computer vision

  • Analyze medical data for insights, diagnostics, and predictive modeling

  • Self-paced, online learning with weekly live support sessions

  • Understand ethical responsibilities when working with healthcare data

  • Connect with professionals in healthcare, data science, and AI fields