YoVDO

Build AI Apps with Azure Database for PostgreSQL

Offered By: Microsoft via Microsoft Learn

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Machine Learning Courses Sentiment Analysis Courses Generative AI Courses Data Summarization Courses Semantic Search Courses

Course Description

Overview

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  • Module 1: Use 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.

  • Module 2: Learn to 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.

  • Module 3: Learn to 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.

  • Module 4: Learn how to 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.

  • Module 5: Learn to 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.

  • Module 6: Learn how to 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.

  • Module 7: Learn how to 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.


Syllabus

  • Module 1: Module 1: Get started with generative AI in Azure Database for PostgreSQL
    • Introduction
    • Understand generative AI language models
    • Describe the Azure AI extension
    • Explore the Azure OpenAI schema
    • Review the Azure Cognitive schema
    • Examine the Azure Machine Learning schema
    • Exercise-Explore the Azure AI extension
    • Knowledge check
    • Summary
  • Module 2: Module 2: Enable semantic search in Azure Database for PostgreSQL
    • Introduction
    • Understand semantic search
    • Store vectors in Azure Database for PostgreSQL
    • Create embeddings with the Azure AI extension
    • Exercise - Generate vector embeddings with Azure OpenAI
    • Explore semantic search use cases
    • Exercise - Create a search function for a recommendation system
    • Knowledge check
    • Summary
  • Module 3: Module 3: Summarize data with Azure AI Services and Azure database for PostgreSQL
    • Introduction
    • Explain extractive summarization
    • Explore abstractive summarization
    • Exercise - Perform extractive and abstractive summarization
    • Knowledge check
    • Summary
  • Module 4: Module 4: Perform sentiment analysis and opinion mining with Azure Database for PostgreSQL
    • Introduction
    • Explore sentiment analysis
    • Describe opinion mining
    • Exercise-Analyze sentiment
    • Knowledge check
    • Summary
  • Module 5: Module 5: Extract insights using Azure AI Language and Azure Database for PostgreSQL
    • Introduction
    • Extract key phrases
    • Recognize entities
    • Recognize personally identifiable information (PII) entities
    • Exercise-Extract insights using the Azure AI Language service
    • Knowledge check
    • Summary
  • Module 6: Module 6: Translate Text with Azure AI Translator and Azure Database for PostgreSQL
    • Introduction
    • Explore the Azure AI Translator Service
    • Translate data in Azure Database for PostgreSQL
    • Exercise-Translate text
    • Knowledge check
    • Summary
  • Module 7: Module 7: Use Azure Machine Learning for inferencing from Azure Database for PostgreSQL
    • Introduction
    • Explore Azure Machine Learning
    • Invoke Azure Machine Learning models
    • Exercise-Perform inference using Azure Machine Learning
    • Knowledge check
    • Summary

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