Get hands-on with Generative AI
Whether you are building a startup or adding to a data-intensive application, taking advantage of a cloud data platform and machine learning and generative AI technologies is key to innovating and gaining a competitive advantage.
Join Snowflake and AWS for an interactive half day session. In this workshop, you’ll learn the basics of building a Streamlit application that uses Snowpark External Access in Snowflake to unlock the power and flexibility of Amazon Bedrock with your Snowflake data. This will allow you to build solutions such as personalised marketing message generation, data augmentation on your Snowflake data (e.g. filling in item descriptions or missing metadata), and analyst-style chatbots deployed securely to your business.
What you’ll do:
- Learn about practical patterns and architectures for GenAI in the Snowflake platform, combining its native Snowflake Cortex features with the AWS ecosystem
- Set up environments in both Snowflake and AWS for GenAI
- Create a function that leverages Snowpark External Access to securely call Amazon Bedrock
- Create a Streamlit app that leverages the above function to generate responses using data from Snowflake and prompts
- Create an agent-based app using Amazon Bedrock Agents that will query data in Snowflake to answer questions using Snowflake’s Cortex APIs
Target Audience
- Data engineers looking to extend their core data workloads with generative AI, while keeping the familiarity of SQL.
- ML practitioners looking to take advantage of Snowflake’s highly scalable compute and data capabilities in their ML and GenAI workflows.
- Data scientists looking to quickly deploy data applications using Streamlit and GenAI, with the safety net of Snowflake’s secure platform, scalability, and ease of use.
Prerequisites:
- Basic familiarity with SQL
Get hands-on with Generative AI
Whether you are building a startup or adding to a data-intensive application, taking advantage of a cloud data platform and machine learning and generative AI technologies is key to innovating and gaining a competitive advantage.
Join Snowflake and AWS for an interactive half day session. In this workshop, you’ll learn the basics of building a Streamlit application that uses Snowpark External Access in Snowflake to unlock the power and flexibility of Amazon Bedrock with your Snowflake data. This will allow you to build solutions such as personalised marketing message generation, data augmentation on your Snowflake data (e.g. filling in item descriptions or missing metadata), and analyst-style chatbots deployed securely to your business.
What you’ll do:
- Learn about practical patterns and architectures for GenAI in the Snowflake platform, combining its native Snowflake Cortex features with the AWS ecosystem
- Set up environments in both Snowflake and AWS for GenAI
- Create a function that leverages Snowpark External Access to securely call Amazon Bedrock
- Create a Streamlit app that leverages the above function to generate responses using data from Snowflake and prompts
- Create an agent-based app using Amazon Bedrock Agents that will query data in Snowflake to answer questions using Snowflake’s Cortex APIs
Target Audience
- Data engineers looking to extend their core data workloads with generative AI, while keeping the familiarity of SQL.
- ML practitioners looking to take advantage of Snowflake’s highly scalable compute and data capabilities in their ML and GenAI workflows.
- Data scientists looking to quickly deploy data applications using Streamlit and GenAI, with the safety net of Snowflake’s secure platform, scalability, and ease of use.
Prerequisites:
- Basic familiarity with SQL
