Share Get Started

All of Us Researcher Workbench On-Demand Training

All of Us Research Program Workshop Series

All of Us Researcher Workbench On-Demand Training

This is a self-directed course. This course was adopted from the AIHES2022 and PRIME programs, sponsored by the AIM-AHEAD Data Science Training Core. All course videos were recorded Fall 2022 as part of the AIHES 2022 Workshop Series. 

Course Objectives

The goal of this course is to learn how the All of Us data and platform, called the Researcher Workbench, can be used to address health disparities with artificial intelligence and machine learning.

Course Structure

This course contains three modules, each composed of five lessons. Each lesson contains a video and accompanying presentation slides.

  • Module 1: AIHES2022 Workshop 
  • Module 2: Deeper Dive into All of Us (PRIME Training Sessions)
  • Module 3: All of Us Applied (PRIME Training Sessions)

How to Register for All of Us Researcher Workbench:

While registering for the Researcher Workbench is optional, attendees who register in advance will have access to the following resources during and after the workshop: 

  • Workshop exercises
  • De-identified, biomedical data from over 300,000 participants
  • Support materials on our User Support Hub (e.g., tutorials, support documentation)
  • Help Desk, Monthly New User Orientation, and Bi-weekly Office Hours for direct support 

To learn more about the All of Us database, please click here. Visit the All of Us “How to Register” page to become a registered user on the Researcher Workbench. Should you have questions during the registration process, please contact the All of Us Support Team (support@researchallofus.org). The All of Us Support Team typically responds to emails in 1-2 business days.

Instrumental Persons

We would like to recognize and express our gratitude to the following people who shared in the creation and implementation of this course:


  • Lina Sulieman, PhD: All of Us Presenter
  • Danielle Wilfong: All of Us Presenter
  • Bradley Malin, PhD: All of Us Presenter
  • Nawar Shara, PhD: Chair of AIHES2022 planning committee, PRIME co-Director
  • Usha Sambamoorthi, PhD: Chair of AIHES2022 Workshop subcommittee, Co-Chair planning committee
  • Toufeeq Ahmed, PhD: Co-Chair of AIHES2022 planning committee
  • Phoebe Nelms, PCMH, CCE: Co-Chair of AIHES2022 planning committee
  • Yelena Yesha, PhD: Co-Chair of AIHES2022 planning committee
  • Omar Aljawfi, PhD: PRIME Curriculum Director
  • Sara Stienecker, MS, MBA: AIHES Coordinator & PRIME Coordinator
  • Tom Whitfield: AIHES Coordinator & PRIME Coordinator
  • Katie Stinson, MLIS: Central Hub Communications Team
  • Jojo Navarro, BFA: Central Hub Communications Team
  • Aidan Hoyal, MSIS, MA: Communications Hub, AIM-AHEAD
  • Zainab Latif, MCS: Communications Hub, AIM-AHEAD 
  • Alexander Libin, PhD: PRIME co-Director

Funding

All of Us trainings are made possible through funding from the AIM-AHEAD Data Science Training Core and from the All of Us Research Program. The Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) program is funded by NIH, Agreement No.: 1OT2OD032581-01. The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.