Build AI Apps with Azure Database for PostgreSQL
This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL - Flexible Server can enable you to build AI-powered apps.
Prerequisites
Before starting this module, you should have experience working with PostgreSQL databases, writing SQL queries, and a general understanding of AI and ML concepts.
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Modules in this learning path
This module explores how to effectively use Azure Database for PostgreSQL - Flexible Server and the Azure AI extension to develop powerful Generative AI applications.
This module explores semantic search, embedding vectors, vector similarity, and using Azure Database for PostgreSQL - Flexible Server with PostgreSQL Vector and Azure AI extensions to generate, store, and query rows with semantic search.
This module will examine how Azure AI Services and the Azure AI extension for Azure Database for PostgreSQL - Flexible Server enable Generative AI summarization techniques for condensing complex content into concise summaries.
This module will explore how Azure AI Services and the Azure AI extension for Azure Database for PostgreSQL - Flexible Server enable sentiment analysis and opinion mining to extract valuable insights from textual data.
This module covers Azure AI Language tools including key phrase extraction, entity recognition, personally identifiable information recognition and redaction, and using Azure Database for PostgreSQL - Flexible Server with Azure AI to access these services.
This module guides you through translating textual data in Azure Database for PostgreSQL - Flexible Server using the Azure AI Translator service. You'll load data into PostgreSQL and translate it into multiple languages.
This module guides you through training and deploying an Azure Machine Learning model using automated machine learning. Then, you'll call the model directly from Azure Database for PostgreSQL - Flexible Server.