• MSDS Capstone: Industry Project Proposal

    Complete this form to submit an industry capstone project proposal.

  • Deadline: Please complete the form by July 15th to be considered for the Fall 2026 

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    CAPSTONE COURSE OVERVIEW 

    The Columbia University MS in Data Science Capstone Program is a semester-long sponsored partnership opportunity that connects organizations with teams of Columbia MS in Data Science students to work on real-world data science challenges.


    Through the program, sponsors have the opportunity to collaborate with students on applied projects involving machine learning, AI, analytics, modeling, engineering, and other data-driven initiatives relevant to their organization. Capstone projects allow sponsors to explore innovative approaches to business, operational, research, and technical problems while engaging directly with Columbia’s data science ecosystem.


    Student teams work under the guidance of industry mentors and Columbia instructional team throughout the semester.


    Capstone projects are designed to:

    1. Address modeling, computational, engineering, and analytical challenges in data science
    2. Explore and experiment with modern data science and AI technologies in real-world applications
    3. Develop actionable insights, models, prototypes, visualizations, and other project deliverables aligned with sponsor objectives

    At the conclusion of the semester, sponsors are invited to participate in the Capstone Showcase and Poster Session, where student teams present their findings, recommendations, models, and project outcomes to industry representatives, faculty, and the broader Columbia community. These presentations can provide valuable insights to help inform future organizational strategy, innovation initiatives, and data-driven decision-making, while also creating opportunities to engage with emerging talent and strengthen visibility within the Columbia ecosystem.

  • STRUCTURE

    • Duration: 14 weeks (Spring or Fall Semester)
    • Student Team: 4 - 6 students per team will work on the project 
    • Columbia will provide GCP credits of $100 per student and Anthropic Claude credits for use in the course. Sponsors are responsible for covering any additional costs. If you have questions about this, please reach out to dsi-capstone@columbia.edu
    • Student Workload: Students are enrolled in multiple courses during the capstone course, and are expected to spend about 10 hours per week on the capstone course. Students should not continue working on the project once the program concludes.  
    • A Columbia faculty advisor is also paired with the team working on the project
    • Mentors will be matched with their teams during week 2.
  • Is your company a DSI Industry Catalyst Network (ICN) member?*

  • Please Note

    Participation in the MSDS Capstone is provided as a benefit for DSI Industry Catalyst Network (ICN) Members.

    Non-member participation: Proposals from non-members are also welcome for submission. Accepted projects incur a fee of $30,000, with 50% payable upon acceptance and the final 50% due following project completion.

    To learn more about non-member pricing or to explore ICN membership opportunities please contact dsi-partnerships@columbia.edu.

    • Proposer Contact Information 
    • Mentor Requirements and Expectations 

    • MENTOR REQUIREMENTS AND EXPECTATIONS

       

      A dedicated industry mentor is a key component of a successful capstone engagement and helps ensure strong collaboration between the sponsoring organization and the student team. Each participating organization is asked to designate at least one mentor who will serve as the primary point of contact throughout the semester.

      Mentors provide domain expertise, strategic guidance, business context, and ongoing feedback to help shape the direction and success of the project. Active mentor engagement also helps ensure that project outcomes remain aligned with organizational priorities and deliver meaningful value to the sponsoring organization.

      In addition to working closely with the student team, mentors collaborate with the Columbia instructional team and faculty advisor to support project execution and evaluate overall project outcomes throughout the semester.

       

      Expectations

      • Mentors are expected to schedule a weekly 30–60 minute meeting with students during the program. Total time commitment 1-2 hours per week.
      • Mentors should provide feedback on the project and ensure students have access to the data and any other materials necessary for them to complete the project.
      • Each project must have at least one dedicated mentor that will be available to meet with the students on a weekly basis for the duration of the semester. There may be more than one mentor.
      • If excess computing resources are required for the project, the company will be responsible for the cost.
    • Add another Mentor?*
    • Add another Mentor?*
    • Mentor and company contact information should be entered as completely as possible for all relevant participants.
    • Project Proposal 

    • The Capstone is an integral part of Columbia University’s Masters in Data Science program. The Capstone program requires:

       

      CAPSTONE REQUIREMENTS

      1. Defined Problem: A clear description of the data science problem to be addressed that is capable of being completed within a 4 month period. 
      2. Current challenge: The problem should reflect a business problem currently faced by the sponsor.
      3. Datasets: Data sets must be in a format that is already prepped and clean for the project described. Data should not include confidential data. Students must be able to access the data at the start of the semester in order to avoid significant delays. Data accessibility by the beginning of the semester is critical to the overall success of the project. 
      4. Timeline: Over the course of the semester, there should be key milestones and deliverables set for the students to meet and receive feedback.
      5. Outcomes: Projects should aim to address a clearly actionable business, operational, or research outcome. 
      6. Technical Approach: The project must include a summary of the methods and tools to be used as well as a modeling component 

    • Project Proposal

    • Proposal Period*
    • What area of data science does the project focus on?*
    • Project plan includes methods and tools to be used in the project. Check all that apply:*
    • Are you open to working with more than one team on this project?*

    • Dataset Ownership, Access, and Availability

    • Dataset is available and sufficient for analysis*
    • Will students have permission to use the data?*
    • Do you already have written internal permission to share the data?*
    • What is the current state of the data?*
    • Does the dataset contain personal or sensitive information (e.g., PII, health data)?*
    • Is the data publicly available?*
    • How will the dataset be made available?*
    • Type of Data (check all that apply)*

    • Data Science Methods and Computational Needs

    • Data Science Methods & Techniques to be used*
    • Computational Needs*

    • Deliverables, Timeline, and Evaluation

    • Deliverables (check all that apply)*
    • Rows
    • Acknowledgement and Signature 

    • Intellectual Property and NDA Policy 

      Please review and intial below. 

    • The Data Science Capstone Course is a required course for the MS in Data Science students. It is University policy that Columbia students maintain ownership of their work when engaging with outside entities as a part of coursework. Columbia University views capstone coursework as work owned by the students and shared with the mentors. Please do not restrict students from openly sharing their project for resume purposes or make the agreements onerous for the student.

    • Students will sign non-disclosure or other agreements or undergo compliance training if your organization requires them to do so. Onboarding must be completed before the start of the semester . Please note that Columbia University treats graduate students as autonomous agents and the university is not able to enter into agreements directly with you. If this is an issue or if you have any questions, please reach out to dsi-capstone@columbia.edu 

    • Consent for Public Sharing 

      As part of DSI’s Capstone storytelling and student-facing communications, we regularly share highlights of Capstone projects on our website, social media, and other channels. By participating in the program, you acknowledge that your project may be publicly referenced or featured, and you consent to the inclusion of your organization’s name, project title, and student outcomes, pending review. Please note that prior to sharing, we will collaborate with your organization's communications team to ensure that we align with your organization's guidelines.

    • Would you be open to serving as a guest lecturer for the course and/or presenting project outcomes at the Capstone Showcase/Poster Session event?*

    • Acknowledgement:

      I, on behalf of {q19_textbox17}, agree to sponsor a capstone for the semester and have confirmed that the requisite data will be available and accessible by the start of the semester.

    • Date*
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