After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Most of your organization's knowledge is locked inside tables, PDFs, and documents that only technical users can query. What if anyone could just ask? In this course, you'll build generative AI apps on Snowflake that let people talk to their data in plain language. You'll learn when to reach for RAG, hybrid search, or text-to-SQL, then build working chatbots with Cortex Search for documents and Cortex Analyst for tables, each with a Streamlit front end. By the end, you'll turn raw data into answers the whole business can use.
Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Differentiate when to use RAG, hybrid search, and text-to-SQL based on whether the source data is structured or unstructured.
- Determine how to load, parse, and chunk documents into a Cortex Search service that powers a RAG application over unstructured data.
- Recognize best practices for delivering a conversational app to business users with a Streamlit front end.
Prerequisites
Curriculum
Course outline
1
Introduction to building conversational apps with data
In this chapter, learn how to choose between RAG, hybrid search, and text-to-SQL for your data and sketch the architecture of a conversational app on Snowflake.
- Getting answers from data50 XP
- Getting answers from data: Using RAG50 XP
- Getting answers from data: Using text-to-SQL50 XP
- What we will build: Success in this course50 XP
- Reference documentation on COMPLETE50 XP
- Querying unstructured data: RAG50 XP
- Querying Unstructured Data: Hybrid Search50 XP
- Querying structured data: Text-to-SQL50 XP
- Setting up your environment50 XP
- Let's dive in50 XP
- Chapter 1 review - Question 150 XP
- Chapter 1 review - Question 250 XP
- Chapter 1 review - Question 350 XP
- Chapter 1 review - Question 450 XP
- Chapter 1 review - Question 550 XP
2
Finding answers from unstructured data with Cortex Search
In this chapter, learn how to build a RAG app with Cortex Search by loading, parsing, and chunking documents, measuring answer quality, and shipping it with Streamlit.
3
Answer questions from structured data with Cortex Analyst
In this final chapter, learn how to turn structured tables into a natural-language interface with Cortex Analyst, using a semantic model to generate accurate SQL and serve answers through a Streamlit app.
R
Building Generative AI Apps to Talk to Your Data
Course
Complete
