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Microsoft

Execute queries and build a Generative AI application with Azure Cosmos DB

Microsoft via Microsoft Learn

Overview

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  • Author queries for Azure Cosmos DB for NoSQL using the SQL query language.

    After completing this module, you'll be able to:

    • Create and execute a SQL query
    • Project query results
    • Use built-in functions in a query
  • Create SQL queries for Azure Cosmos DB for NoSQL that uses subqueries or cross-products.

    After completing this module, you'll be able to:

    • Implement a correlated subquery
    • Create a cross-product query
  • Build advanced Generative AI application with Python and Azure Cosmos DB for NoSQL.

    After completing this module, you'll be able to:

    • Build a Generative AI application capable of interacting with private data using Python and Azure Cosmos DB for NoSQL.
    • Efficiently retrieve and store vectors in Azure Cosmos DB for NoSQL.
    • Perform similarity searches using Azure Cosmos DB for NoSQL.
    • Integrate data and AI models using LangChain orchestration to create intelligent and adaptable Generative AI application.

Syllabus

  • Query the Azure Cosmos DB for NoSQL
    • Introduction
    • Understand NoSQL query language
    • Create queries with NoSQL
    • Project query results
    • Implement type-checking in queries
    • Use built-in functions
    • Execute queries in the SDK
    • Exercise: Execute a query with the Azure Cosmos DB for NoSQL SDK
    • Knowledge check
    • Summary
  • Author complex queries with the Azure Cosmos DB for NoSQL
    • Introduction
    • Create cross-product queries
    • Implement correlated subqueries
    • Implement variables in queries
    • Paginate query results
    • Exercise: Paginate cross-product query results with the Azure Cosmos DB for NoSQL SDK
    • Knowledge check
    • Summary
  • Build Generative AI applications with Azure Cosmos DB
    • Introduction
    • Configure the Vector Search and storage feature of Azure Cosmos DB NoSQL
    • Exercise - Enable the Azure Cosmos DB for NoSQL Vector Search feature
    • Generate embeddings using Azure OpenAI Service
    • Exercise - Generate vector embeddings with Azure OpenAI and store them in Azure Cosmos DB for NoSQL
    • Build Generative AI applications with Azure Cosmos DB NoSQL and Python
    • Perform vector searches using Azure Cosmos DB for NoSQL from a Generative AI application
    • Exercise - Build a Generative AI application with Python and Azure Cosmos DB for NoSQL
    • Integrate LangChain orchestration to improve efficiency and code maintainability in a Python Generative AI application
    • Exercise - Implement RAG with LangChain and Azure Cosmos DB for NoSQL Vector Search
    • Knowledge check
    • Summary

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