> For the complete documentation index, see [llms.txt](https://hacktoberfest-handbook.mlh.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hacktoberfest-handbook.mlh.com/hack-days-partner-modules/partner-challenge-snowflake-coco.md). # Snowflake Snowflake supports Major League Hacking with tools for building data and AI applications. Snowflake CoCo is its AI coding agent for data work, available on the web, desktop, and command line. ## Best Open-Source AI Project with Snowflake Use Snowflake CoCo to find or understand a freely accessible dataset in Snowflake, then build an open-source AI project around it. * Explore the Snowflake Marketplace or Snowflake sample data with CoCo * Use CoCo to understand the dataset, write queries, or create a data pipeline * Build an AI application, agent, analysis, or other useful experience with open-source code Eligible projects combine all three elements: CoCo, a freely accessible Snowflake dataset, and open-source or open-weight AI. ## Participant Resources Share these resources before and during the Fest: * [Snowflake CoCo overview](https://docs.snowflake.com/en/user-guide/cortex-code/cortex-code) * [Snowflake CoCo trial](https://signup.snowflake.com/cortex-code/) * [Explore Snowflake Marketplace listings](https://docs.snowflake.com/en/collaboration/consumer-listings-exploring) * [Snowflake sample datasets](https://docs.snowflake.com/en/user-guide/sample-data) ## Opening Slides Use the Hacktoberfest Snowflake opening slides included in your event onboarding. Make a copy and edit only the host-controlled slides. ## Choosing the Winner The project must use open-source or open-weight AI, use a freely accessible Snowflake dataset, and be published in a public GitHub repository with an open-source license. Ask the team to identify the dataset and show how CoCo helped them explore the data or build the project. ## Expected Prize **Arduino Tiny Machine Learning Kit** Check your event's onboarding materials before sharing prize details with participants, as availability may vary by region. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://hacktoberfest-handbook.mlh.com/hack-days-partner-modules/partner-challenge-snowflake-coco.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.