Building Conversational AI Apps to Talk to your Data

Welcome to the companion repo for Building Conversational AI Apps to Talk to your Data. This GitHub repo contains all of the code you need to to complete the course.

In this course, you’ll learn how to build conversational AI applications that let users interact with their data, whether structured in tables or unstructured in documents, using natural language. Designed as the next step after our Intro to GenAI course, this course focuses on building practical applications with Snowflake Cortex, including Cortex Search for unstructured data and Cortex Analyst for structured data.
You'll gain the skills to connect these applications to real data sources, build robust backends, and deliver user-friendly interfaces for GenAI apps using Streamlit. By the end, you’ll know how to design, build, and deploy end-to-end GenAI apps that democratize access to the insights previously locked away in data.

This course is built for developers, data scientists, and ML engineers looking to bring natural language interfaces into their organizations.

What You’ll Learn:

• Understand techniques for interacting with data including Text-to-SQL, RAG, and hybrid search—and when to use each
• How to build a high quality, up-to-date RAG using Cortex Search
• How to build text-to-SQL applications using Cortex Analyst that answer questions from structured data in natural language
• How to build a frontend for your RAG and Text to SQL applications using Streamlit