All use of Scientific Computing and Data resources in publications and presentations must acknowledge Mount Sinai’s CTSA award. Click here

AIR·MS Training

AIR·MS and Data2Evidence Training

Fall 2026 Data2Evidence Cohort Query Tool Training: Slides and Recordings Now Available! 
Fall 2026 Data2Evidence training has concluded and will return in Spring 2027. Recordings from the most recent sessions are available at the links below:
 
Data2Evidence Office Hours
  • Additional Data2Evidence office hours will be announced in November 2026!
 
Data2Evidence Additional Information

Fall 2026 AIR‧MS Training Sessions: Slides and Recordings Now Available! 

Fall 2026 AIR‧MS training has concluded and will return in Spring 2027. Recordings from the most recent sessions are available at the links below:

___________________________________________________________

Session 1 — Getting Started with AIR·MS: Health Data Fundamentals

SLIDES AND VIDEO NOW AVAILABLE: (powerpoint slides) (video recording) 

This introductory session will help you understand how clinical data moves into AIR·MS and how to begin working with it.

You’ll learn how to:

  • Understand the flow of data from Epic into AIR·MS
  • Recognize common challenges and pitfalls when working with clinical data
  • Perform basic exploratory data analysis (EDA) in AIR·MS
  • Work through a live Jupyter Notebook demonstration

Training materials

Prerequisites

Some hands-on portions of the training require access to Minerva and the AIR·MS OMOP De-ID dataset.

If you don’t already have access:

  1. Make sure you have an ISMMS School Network Account.
    If you need one, request it through SailPoint by selecting “School Network Account.”
  2. Request a Minerva account using the Minerva account request form.
    If you are not a PI, your PI will need to provide approval by email.
  3. Request access to the AIR·MS OMOP De-ID dataset through SailPoint. Select “AIR.MS Production MSDW OMOP De-ID (MSSM).”
    See the AIR·MS data access guide for detailed instructions.
  4. For additional information, visit AIR·MS: Getting Started.

Important: To access SailPoint, you must be connected to the Mount Sinai network, either on campus or through VPN.

___________________________________________________________

Session 2 — From AI Agents to AIR·MS: Leveraging Large Language Models

What you’ll learn

Discover how locally hosted, open-source large language models (LLMs) can help with health data exploration in AIR·MS.

Topics include:

  • ChatAI demonstration
  • Using Ollama and AIR·MS with Python
  • Introduction to SQL
  • Using LLMs to help write and refine SQL queries

Training materials

Prerequisites

Participants should have Minerva and AIR·MS access before attending so that there is enough time for account and dataset permissions to be processed.

Minerva requires the Secure Shell (ssh) protocol and Microsoft Azure Multi-Factor Authentication (MFA). You can authenticate using one of the following methods:

  • App Push: A notification sent to the Microsoft Authenticator app on your mobile device.

  • Phone Text/Call: A one-time passcode sent via SMS or an automated phone call.

  • App Passcode: A rolling six-digit code generated within the Authenticator app.

  • Note: If you have not yet configured your MFA preferences, please visit the Microsoft MFA Setup Portal.

Connection Steps

  1. VPN: If you are off-campus, you must first connect to the Mount Sinai VPN.
  2. SSH Command: Open your terminal or an SSH client like PuTTY.
  3. Authentication: * Username: Use your standard Sinai credentials.

    • Password: Enter your Sinai password.

    • MFA Challenge: Complete the second-step verification using your chosen Azure MFA method.

SSH command: ssh your_userid@minerva.hpc.mssm.edu

For detailed instructions and troubleshooting, please refer to the official Logging In documentation.

___________________________________________________________

Session 3 — Advanced AIR·MS: Data Modalities & AI/ML Applications

What you’ll learn

Take a deeper look at AIR·MS and its capabilities for multimodal health data research and AI/ML applications.

The session will feature lightning talks and demonstrations covering:

  • OMOP clinical data
  • Pathology
  • Radiology
  • Echocardiography
  • Mount Sinai Million
  • Advanced applications of AIR·MS for research

Archive AIR‧MS and Data2Evidence Training Sessions

Recordings and slides from prior training sessions are available below.

Jupyter Notebooks and R Resources to Get You Started:

Spring 2026 Data2Evidence Training Sessions

May 2026

Training slides and recordings from our two Spring sessions are now available here:
Session 1 (SLIDES) (VIDEO RECORDING)
Data2Evidence can be accessed at d2e.airms.mssm.edu by all existing Mount Sinai and Icahn School of Medicine users on site or via VPN. It does not require separate registration currently.
For additional information about how Data2Evidence may benefit your research visit our website: https://labs.icahn.mssm.edu/minervalab/d2e-data2evidence-cohort-query-tool/

Spring 2026 AIR‧MS Training Sessions

  • Tuesday April 7: Getting Started with AIR·MS: Health Data Fundamentals SLIDES AND VIDEO RECORDING
  • Tuesday April 14: From AI Agents to AIR·MS: Leveraging Large Language Models SLIDES AND VIDEO RECORDING
  • Tuesday April 21: Advanced AIR·MS: Deep Dive into Data Modalities and AI/Machine Learning (ML) Applications SLIDES AND VIDEO RECORDING

Fall 2025 Inaugural AIR‧MS Town Hall

The Fall 2025 Inaugural AIR‧MS Town Hall is now available (powerpoint slides) (video recording).

 

Fall 2025 AIR‧MS Training Sessions

 

Spring 2025 Inaugural AIR‧MS Training Session

The Inaugural AIR‧MS Training video is now available here.