What we will build: Success in this course
1. What we will build: Success in this course
Welcome back. Now that we've done a high-level overview of the course, let's talk about who this course is best suited for. This course is open to anybody, but it's going to be best suited for AI builders, such as data scientists, machine learning engineers, or AI builders who are interested in developing applications and practices that unlock unstructured data and fight a direct connection between users and the data that they want to ask questions of. To succeed in this course, you should have experience with Snowflake, Python, and SQL. A basic understanding of generative AI concepts will be helpful as well. Our intro to generative AI course covered a lot of information, and I highly recommend taking it after you've completed this course. It's a great course taught by my friend Vino, but the only part from it that we'll need is how to do text generation using the Cortex complete function. If you would like to learn more about the complete function before we get started, I've left a link to documentation with more details in the reading after this video. If you're completely new to Snowflake, we recommend that you start with our intro course, Intro to Snowflake for Devs, Data Scientists, and Data Engineers. This will give you a good foundation on the Snowflake environment and operating within it. Now let's talk about the new skills you'll have at the end of this course. In module 1, we'll understand the different architectures required for building conversational apps with structured and unstructured data. We'll then learn how to implement these architectures using the Snowflake platform. In module 2, we'll build a RAG app using Cortex Search in a Snowflake Notebook that will answer questions from your unstructured data. You'll learn how to parse and chunk PDF documents, create a Cortex Search service, and use that to build an app that can talk to your documents using RAG. In module 3, we'll build a text to SQL application using Cortex Analyst. In a Snowflake Notebook, that will answer questions from structured Snowflake data tables. This app will also live on a conversational front-end. I gave you a preview for this earlier. Let's talk about what this course will not cover. This course is not a highly theoretical course. Think of this as an applied course where you'll get hands-on experience with the material and build something tangible. You'll come out of this course with built examples of how to deploy these skills. In this module, we introduced how to create a RAG app with Cortex Search for unstructured data, and how we'll use text to SQL with Cortex Analyst to query our structured data. When used together, we can query our entire data volume. In the next video, we'll dive a little deeper looking at how we get answers from unstructured data using RAG. Once we're done, we'll look at under-the-hood elements that we need to be aware of to get answers from structured data using text to SQL. See you in the next video. Thank you for watching.2. Let's practice!
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