Women in Data Science (WiDS)
  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • WiDS Regional Events 2023
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Datathon Details
    • Datathon Resources >
      • Datathon Press Release
    • WiDS Datathon Workshops 2023
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Next Gen >
      • Next Gen Resources
      • Next Gen Committee
Photo credit: Dana Quigley
Identifying and Removing Barriers for Women to
​Pursue Graduate Degrees in Data Science and AI
Download the white paper
Women are significantly underrepresented in U.S. graduate school programs focused on Data Science (DS) and Artificial Intelligence (AI). In this paper, we seek to inform academia, industry, government, and nonprofits about:
  • The current situation and trends in the workforce and in education
  • The common barriers that women experience when preparing for, entering, or completing graduate programs
  • A suite of possible programmatic approaches to effectively reduce barriers and increase women’s participation to a critical threshold
Executive Summary
WiDS Academy
The WiDS Academy a proposed program in which partner colleges and universities would deliver program elements to their students with central support from WiDS. It would provide programming that intervenes early, reaches a broad population, and addresses barriers throughout a student’s undergraduate years.

The goal is to increase awareness, facilitate consideration, and promote preparedness for graduate study in DS/AI. 
Learn More
% of CS Master's Students
​that are U.S. Women
% of U.S. Data Scientists
​with Graduate Degrees
Proposed representation
​% threshold (30 x 30)

Initiatives

Conference
Ambassador Program
Datathon
Podcast
Workshops 
Next Gen

Follow Us

LinkedIn
Twitter
Facebook
Instagram
YouTube
​Blog

connect

LinkedIn Group
Facebook Group
subscribe
donate

© 2022 Women in data science. Women in Data Science is a Registered trademark of Stanford University. 

  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • WiDS Regional Events 2023
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Datathon Details
    • Datathon Resources >
      • Datathon Press Release
    • WiDS Datathon Workshops 2023
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Next Gen >
      • Next Gen Resources
      • Next Gen Committee