AI-3019: Build AI Apps with Azure Database for PostgreSQL
Enroll in the Build AI Apps with Azure Database for PostgreSQL Course (AI-3019) to dive into the world of generative AI application development. Many developers encounter challenges in effectively implementing AI functionalities, leading to underutilization of the PostgreSQL database capabilities. This course will equip you with the tools and techniques needed to successfully integrate AI into your database applications.
Instructor
AI-3019: Build AI Apps with Azure Database for PostgreSQL Training
AI-3019: Build AI Apps with Azure Database for PostgreSQL
The Build AI Apps with Azure Database for PostgreSQL Course (AI-3019) offers a comprehensive exploration of generative AI and its application in PostgreSQL. Participants will learn to leverage the azure_ai extension for creating AI-driven applications, enabling semantic search, summarization, and sentiment analysis. The course covers essential techniques for extracting insights and translating text using Azure AI services. Hands-on labs enhance learning by allowing participants to implement and test AI features within Azure Database for PostgreSQL, making this training crucial for developers and data scientists interested in AI integration.
Target Audience
Database Developer
Database Administrator
IT Professional
Prerequisites
Required:
Before starting this course, you should have experience working with PostgreSQL databases, writing SQL queries, and a general understanding of AI and ML concepts.
Course Objectives
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
1) 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
Lab: Explore the Azure AI extension
2) 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
Lab: Generate vector embeddings with Azure OpenAI
Lab: Create a search function for a recommendation system
3) 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
Lab: Perform extractive and abstractive summarization
4) 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
Lab: Analyze sentiment
5) 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
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
Lab: Extract insights using the Azure AI Language service
6) 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
Lab: Translate text
7) 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
Lab: Perform inference using Azure Machine Learning
The Build AI Apps with Azure Database for PostgreSQL Course (AI-3019) offers a comprehensive exploration of generative AI and its application in PostgreSQL. Participants will learn to leverage the azure_ai extension for creating AI-driven applications, enabling semantic search, summarization, and sentiment analysis. The course covers essential techniques for extracting insights and translating text using Azure AI services. Hands-on labs enhance learning by allowing participants to implement and test AI features within Azure Database for PostgreSQL, making this training crucial for developers and data scientists interested in AI integration.
Target Audience
Database Developer
Database Administrator
IT Professional
Prerequisites
Required:
Before starting this course, you should have experience working with PostgreSQL databases, writing SQL queries, and a general understanding of AI and ML concepts.
Course Objectives
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
1) 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
Lab: Explore the Azure AI extension
2) 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
Lab: Generate vector embeddings with Azure OpenAI
Lab: Create a search function for a recommendation system
3) 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
Lab: Perform extractive and abstractive summarization
4) 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
Lab: Analyze sentiment
5) 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
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
Lab: Extract insights using the Azure AI Language service
6) 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
Lab: Translate text
7) 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
Lab: Perform inference using Azure Machine Learning
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