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Overview

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.
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What You'll Learn

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

Who Should Attend

N/A
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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.

Learning Journey

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1. Get started with generative AI in Azure Database for PostgreSQL

This module explores how to effectively use Azure Database for PostgreSQL - Flexible Server and the Azure AI extension to develop powerful Generative AI applications.

Click here to know more

2. Enable semantic search in Azure Database for PostgreSQL

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.

Click here to know more

3. Summarize data with Azure AI Services and Azure database for PostgreSQL

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.

Click here to know more

4. Perform sentiment analysis and opinion mining with Azure Database for PostgreSQL

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.

Click here to know more

5. Extract insights using Azure AI Language and Azure Database for PostgreSQL

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.

Click here to know more

6. Translate Text with Azure AI Translator and Azure Database for PostgreSQL

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.

Click here to know more

7. Use Azure Machine Learning for inferencing from Azure Database for PostgreSQL

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.

Click here to know more

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    Microsoft-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

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    Microsoft certification exams are designed to assess your knowledge and skills in specific Microsoft technologies and solutions.

    Exams typically consist of multiple-choice, multiple-select, and case study questions, and some may include lab simulations to evaluate your practical skills.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Microsoft certification valid for?

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    However, Microsoft Applied Skills credentials and Fundamentals certifications do not expire.

    Note: Certification requirements and policies may be updated by Microsoft from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

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