Course curriculum

    1. Welcome and Introductory instructions

    2. How to use this course

    3. Course Syllabus

    4. Course Competencies

    1. Module Description

    2. Pre-Reading 1: Electronic Health Record Data Quality Assessment and Tools: a Systematic Review

    3. Pre-Reading 2: Artificial Intelligence—From Starting Pilots to Scalable Privilege

    4. Pre-Reading 3: Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records

    5. Pre-Reading 4: How Do You Test AI in Medicine

    6. Session 1 Exercises

    7. Session 1 Exercises and Data Files

    8. Module 1 - Live Call Recording

    1. Module Description

    2. Video Module 2 - Data Science Pipeline

    3. Video Module 2 - Descriptive Analysis

    4. Video Module 2 - Data Information Quality

    5. Weka Data Mining Tutorial

    6. Getting Started with Orange Tutorial Videos

    7. Pre-Reading 1: Fundamentals of Research Data and Variables: The Devil Is in the Details

    8. Pre-Reading 2: Basic Introduction to Statistics in Medicine, Part 1: Describing Data

    9. Synthetic Data Exercise - Documents 1 and 2

    10. Module 2 - Live Call Recording

    1. Module Description

    2. Pre-Reading 1: Meeting the Artificial Intelligence Needs of U.S. Health Systems

    3. Pre-Reading 2: Respiratory Support Status from EHR Data for Adult Population: Classification, Heuristics, and Usage in Predictive Modeling

    4. Tutorial Videos 1: Predictive Modeling

    5. Tutorial Videos 2: Clustering

    6. Module 3 Live Call Recording

    1. Module Description

    2. Session 4 Reading 1

    3. Session 4 Reading 2

    4. Module 4 - Live Call Recording

About this course

  • Free
  • 32 lessons
  • 4.5 hours of video content

This course will teach you how to:

  • Integrate advanced AI models into the data science lifecycle.

  • Learn how to select and use data science tools effectively.

  • Identify and understand the best data sources for various AI applications.

  • Select and apply the most effective strategies for implementing large language models (LLM) models in health research practices.

  • Learn about processes behind AI funding mechanisms, and to secure funding for AI-related projects.

Instructor(s)