- 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.
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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