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Build AI Apps with Azure Database for PostgreSQL (AI-3019)

PostgreSQL - Flexible Server can enable you to build AI-powered apps.

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.

GK# 834070 Vendor# AI-3019
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Who Should Attend?

Intermediates and developers who wants to build AI Apps with Azure Database for PostgreSQL.

What You'll Learn

Students will learn to,

  • Get started with generative AI in Azure Database for PostgreSQL
  • Enable semantic search in Azure Database for PostgreSQL
  • Summarize data with Azure AI Services and Azure database for PostgreSQL
  • Perform sentiment analysis and opinion mining with Azure Database for PostgreSQL
  • Extract insights using Azure AI Language and Azure Database for PostgreSQL
  • Translate Text with Azure AI Translator and Azure Database for PostgreSQL
  • Use Azure Machine Learning for inferencing from Azure Database for PostgreSQL

Course Outline

Get started with generative AI in Azure Database for PostgreSQL

  • Examine the concepts of generative AI and large language models and explore how they can be used to build rich AI applications.
  • Evaluate the capabilities of azure_ai extension for PostgreSQL.
  • Install and explore the azure_ai extension in an Azure Database for PostgreSQL - Flexible Server database.

Enable semantic search in Azure Database for PostgreSQL

  • Examine the concepts of semantic search & embedding vectors.
  • Understand the difference between lexical search & semantic search.
  • Evaluate the capabilities provided by the azure_ai extension for PostgreSQL.
  • Install and explore the vector and azure_ai extensions in an Azure Database for PostgreSQL - Flexible Server database.

Summarize data with Azure AI Services and Azure database for PostgreSQL

  • Evaluate the summarization techniques available through Azure AI Services and the azure_ai extension.
  • Examine the differences between extractive, abstractive, and query-focused summarization.
  • Apply Generative AI summarization techniques to data in a PostgreSQL database to gain practical experience using Azure AI Services and the azure_ai extension for summarization.

Perform sentiment analysis and opinion mining with Azure Database for PostgreSQL

  • Explore the fundamentals of sentiment analysis and how it can be leveraged to gain insights into user sentiments and emotions.
  • Describe opinion mining techniques to identify sentiments related to specific attributes.
  • Apply sentiment analysis to user reviews in a PostgreSQL database using the azure_ai extension.

Extract insights using Azure AI Language and Azure Database for PostgreSQL

  • Examine the concepts of key phrase extraction, entity recognition, and PII (personally identifiable information recognition) recognition.
  • Understand the capabilities provided by the azure_ai extension for PostgreSQL to access Azure AI Language.
  • Install the azure_ai extension in an Azure Database for PostgreSQL - Flexible Server database, and use it to extract key phrases, recognize entities in text, and redact PII.

Translate Text with Azure AI Translator and Azure Database for PostgreSQL

  • Learn how to translate documents using the Azure AI Translator.
  • Learn how the Azure AI extension enables seamless interaction between Azure Database for PostgreSQL - Flexible Server and Azure AI Translator.
  • Understand one way to translate documents automatically as part of record insertion.

Use Azure Machine Learning for inferencing from Azure Database for PostgreSQL

  • Learn how to train and deploy an Azure Machine Learning model using automated machine learning.
  • Learn how to invoke deployed Azure Machine Learning models from Azure Database for PostgreSQL - Flexible Server.
  • Learn how to generate predictions for each row in an Azure Database for PostgreSQL - Flexible Server table.

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.