Welcome to Building Your Own Database Agent, built in partnership with Microsoft. In this course, you'll learn how LLMs can interact with structured data like tabular data or SQL databases. This is very useful when you're building a system to answer questions using data sources with tables of data, rather than needing to find maybe an analyst to translate a question to a SQL database query, you see how a database agents can automatically input a question and generate a sequence of actions. This function calls to retrieve the relevant data. Specifically, in this course, you learn how to build your own AI agent to interact with tabular data and SQL databases. Along the way, you'll learn about some of the key building blocks for agents and will be using the LangChain agents framework. I'm delighted that our instructor for this course is Adrian Gonzalez Sanchez. He is a data AI specialist at Microsoft, teaches at the University level, and is also author of the Azure OpenAI O'Reilly book. Thanks, Andrew. I'm very excited to be here. In this course, you will learn how to deploy LLMs to build your AI agent. Implement RAG with tabular data. Develop your own database agent. Build a function calling system, integrate Azure OpenAI assistance API. You'll go through these concepts using the Azure OpenAI service and LangChain. Although we'll be using a database agent as a running example, these components are useful for building any other agents as well. So database agents are an exciting breakthrough for how we analyze data, is letting people interact with complex datasets without needing to learn query languages like SQL, so that you can have an LLM perform requests to a database for you, regardless of the database provider, data model, or type language. Using an LLM as an extraction layer on top of the database is one of the new frontiers for data democratization within many companies, and perhaps you could bring this to fruition for your company or for applications you're working on. I mean, how exciting is that? Further, I see agents as a rapidly growing category with in terms of AI, and you also learn about key components to agents and best practices for assembling these components into draw this system. Many people have worked to create this course from the Microsoft side I'd like to thank Jorge Garcia Ximenez, Agustine SantaMaria, Arancha Diez Garcia and Xiaopeng Li. From DeepLearning.AI, Diala Ezzeddine also contributed to this course. In the first lesson, you will start building your first AI agent with the Azure OpenAI service. So let's go on to the next video to get started.