Registered Student Organizations

CAIDS provides funding to support Registered Student Organizations who want to develop Data and AI literacy-centered events and programming with emphasis on career topics and expanding data science knowledge across Tulane campus. The program aims to strengthen data literacy, expand learning opportunities, and cultivate a vibrant interdisciplinary data science community on campus.


What We Fund

Grants that support a wide range of data science–centered activities, including:
•    Workshops, training sessions, or hackathons on topics and/or methodologies related to Data and AI/ML.
•    Datathons or structured problem-solving competitions related to Data and AI/ML topics and methodologies. 
•    Speaker events, alumni/career panels, or technical talks featuring Data and AI professionals
•    Initiatives that support internships, career readiness, or professional development in data science
•    Activities that enhance student research engagement, including mentorship, research skill-building, and data-focused inquiry
•    Creation of open-source tools, datasets, dashboards, or educational materials

Initiatives/events planned during Love Data Week, and/or throughout the Spring semester that advance datathons, internship and career preparation, research experiences, and Data/AI literacy skill building will be given priority consideration. 


Grant Amounts

There are two ways to participate:

First, CAIDS Affiliate RSOs will receive a grant of $500.00 and agree to put on at least one data event a semester and participating in Love Data Week and the Data Showcase.  RSOs should contact Dr. Howard (jhoward8@tulane.edu) to discuss receiving affiliate status. 
Join our growing list of affiliate RSOs.
•    Tulane Data Collective
•    Tulane AI Society 
Second, any RSOs may apply for a grant of up to $500 per event using the form (RSO  – Collaboration). Funding is awarded based on impact and feasibility. In some circumstances, RSOs may request to host the event at CAIDS student space in HTML 117 (20 people max).

Eligibility

To apply, organizations must:
•    Be a currently registered and active RSO at Tulane. 
•    Have a clear connection to data science and data literacy. All RSO’s are encouraged to apply. 
•    Follow all event planning rules and plan their own event (book their own room, submit paperwork to wave-sync, receive advisor support, host the event themselves). CAIDS does not provide event support. 
•    Demonstrate capacity and technical readiness to deliver the proposed work
Affiliate and Awarded RSOs must:
•    Sign an MOU with CAIDS.  
•    Place CAIDS logos on all sponsored event materials; 
•    Provide social media materials about the event in advance to the CAIDS social media coordinator.
•    Submit a brief final report after the event that includes:  
o    A summary of project activities and outcomes
o    Image from the event, (as appropriate)
o    Materials or artifacts produced (slides, datasets, code repositories, visuals, etc.)
o    A reflection on student learning and community impact
Collaborative proposals between data-focused RSOs and other student groups are encouraged.

How to Apply

Submit the online application form, which includes:
•    A short project description and outreach plan 
•    A proposed timeline and expected outcomes
•    A detailed, itemized budget
•    9 account number
•    Social Media Account Handles 
•    Contact information for project leads and advisor.
 

Selection Criteria

Proposals will be evaluated on:
•    Relevance to data science, data literacy, and AI/ML literacy. 
•    Impact on student learning, community engagement, or campus data culture
•    Alignment with priority areas: datathons, internship/career readiness, and research experiences
•    Feasibility and clarity of the project plan
•    Innovation, creativity, and potential for hands-on learning

 

Currently, we sponsor the following organizations: 

Tulane Data Collective

The Tulane Data Collective is established for the purpose of providing an extracurricular space for students of varying academic and technical backgrounds to:

      1.  Develop and enhance their knowledge of data science and analytics

      2.  Improve data literacy skills through workshops and projects

      3.  Foster career-readiness in data-driven fields by connecting with professionals and participating in hands-on experiences

 

The Tulane Data Collective provides an inclusive space where students of all backgrounds can develop data science skills, work on hands-on projects, and build professional connections in data-driven fields.

 

 

Follow us on Instagram! @tudatacollective

Email us at: tudatacollective@gmail.com.

 

Tulane Artificial Intelligence Society

The Tulane Artificial Intelligence Society is a cross-campus community for learning, building, and debating AI with purpose. All majors and experience levels are welcome. We explore how AI shapes research, industry, and everyday life through beginner-friendly workshops (prompt engineering, agentic AI, media generation), project nights, speaker panels, and conversations about fairness, transparency, and safety. Our core focus spans four pillars: studying AI itself, examining the philosophy of AI (what it is, what it should be, and how it ought to be used), boosting student productivity with practical AI tools, and advancing education with AI to learn more effectively. We connect students with faculty, alumni, and industry mentors to turn curiosity into portfolio-ready projects and career opportunities. 

Join as a member or step into leadership on committees for Technical Projects, Ethics & Social Impact, Professional Development, or Outreach & Inclusion. Together, we build practical skills, think critically about impact, and create AI solutions for Tulane and New Orleans — where students build, think critically, and shape what AI means for their generation. Education & Ethics TAIS exists to enhance our education. 

We help students use AI responsibly to improve research, writing, prototyping, and creativity while upholding academic integrity. We follow Tulane's AI policies and ethical standards: clear disclosure when AI is used, proper citation, privacy-safe practices, and a commitment to fairness and safety. By understanding how AI works — and where it falls short — we become better learners, collaborators, and leaders. Participation or membership in this organization is nondiscriminatory and open to all students regardless of demographic identity."

Instagram: @tulaneaisociety
Linktree: linktr.ee/tulaneaisociety