This emerging blog includes  WiDS (Women in Data Science) Regional Events and Datathon Workshops involving IBMers and WiDS Datathon teams too!

• Short link for this page https://ibm.biz/wids2023-ibm
• Short talk at PyData NYC Relaunch on February 22, 2023 - slides 
• Short Talk at WiDS Stanford 2023 on March 8, 2023 - slides

Upcoming Events:

Best of WiDS at IBM 2023: Talks on Language Models and Foundation Models - Repeated Twice - Will not be recorded 

• 12 Jul 2023 8:00 AM US Eastern- Enroll here https://www.meetup.com/technical-group-hosted-by-ibm/events/293933432/
• 13 Jul 2023 3:30 PM US Eastern - Enroll here https://www.meetup.com/technical-group-hosted-by-ibm/events/293933628/

Best of WiDS at IBM 2023: Talks on Data Science Contests and Careers - Repeated Twice - Will not be recorded 

• 26 Jul 2023 8:00 AM US Eastern- Enroll here https://www.meetup.com/technical-group-hosted-by-ibm/events/293933877/
• 27 Jul 2023 3:30 PM US Eastern - Enroll here https://www.meetup.com/technical-group-hosted-by-ibm/events/293934042/

For more materials and 2023 sessions - please scroll down 

WiDS Regional Events and Datathon Workshops in 2023
With IBMers speaking and/or hosting 

• Jan 6 – Beijing - Datathon Workshop
• Jan 31 – New York @ IBM - Datathon Workshop - Materials and recordings
• Feb 24 –Bengaluru @ IBM - Datathon Workshop
• Mar 8 – Romania
• Mar 10 – UAE
• Mar 17 - Bangalore
• Apr 8 - Bangalore
• Apr 14 – WiDS New York  - A Collaboration between CUNY and IBM -Materials and recordings 
• Apr 19 – Raleigh-Durham @ IBM
• May 4 - San Francisco @ IBM
• May 27 – UAE (hosted at Heriot Watt)
• Jun 6 – Berlin 
• Jun 9 - Tokyo @ IBM
• Jun 9 - Dublin
• Jun 15 - São Paolo @ IBM
  
• Jun 25 - Cairo @IBM - Private Event 

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These WiDS Regional events are an independent events that are organized by  WiDS Ambassadors as part of the annual WiDS Worldwide conference, the WiDS Datathon, and an estimated 200 WiDS Regional Events worldwide. Everyone is invited to attend all WiDS conference and WiDS Datathon Workshop events which feature outstanding women doing outstanding work.