AI-3022: Implement Knowledge Mining with Azure AI Search

Overview The AI-3022: Implement AI Skills in Azure AI Search course equips learners with the expertise to build, enhance, and manage search solutions using Azure I Search. Participants will gain hands-on experience in creating custom AI search applications, integrating advanced search features, and enriching data using Azure AI Language and Machine Learning models. This course covers the full cycle of developing a powerful AI-driven search solution, from data ingestion to search relevance improvement, ensuring participants are prepared to implement scalable and intelligent search systems in Azure. Course Objectives • Build and deploy a comprehensive Azure AI Search solution. • Develop and integrate custom skills to enhance Azure AI Search. • Create and manage a knowledge store for enriched search experiences. • Use Azure AI Language to enrich search indexes with custom classes. • Implement advanced search features, including term boosting and multi-language support. • Leverage Azure Machine Learning models to enhance AI search capabilities. • Integrate external data sources using Azure Data Factory and the push API. • Perform semantic ranking and vector search for improved search accuracy. Target Audience • AI Engineer • Azure Developer Prerequisites • Familiarity with Microsoft Azure • Application development experience with C# or Python Course Outline Create an Azure AI Search solution • Create an Azure AI Search solution • Develop a search application • Lab: Create a search solution Create a custom skill for Azure AI Search • Implement a custom skill for Azure AI Search • Integrate a custom skill into an Azure AI Search skillset • Lab: Implement a custom skill Create a knowledge store with Azure AI Search • Create a knowledge store from an Azure AI Search pipeline • View data in projections in a knowledge store • Lab: Create a knowledge store Enrich your data with Azure AI Language • Use Azure AI Language to enrich Azure AI Search indexes • Enrich an AI Search index with custom classes • Lab: Enrich a search index in Azure AI Search with custom classes Implement advanced search features in Azure AI Search • Improve the ranking of a document with term boosting • Improve the relevance of results by adding scoring profiles • Improve an index with analyzers and tokenized terms • Enhance an index to include multiple languages • Improve search experience by ordering results by distance from a given reference point • Lab: Implement enhancements to search results Build an Azure Machine Learning custom skill for Azure AI Search • Understand how to use a custom Azure Machine Learning skillset • Use Azure Machine Learning to enrich Azure AI Search indexes • Lab: Enrich a search index using Azure Machine Learning model Search data outside the Azure platform in Azure AI Search using Azure Data Factory • Use Azure Data Factory to copy data into an Azure AI Search Index • Use the Azure AI Search push API to add to an index from any external data source • Lab: Add to an index using the push API Maintain an Azure AI Search solution • Use Language Studio to enrich Azure AI Search indexes • Enrich an AI Search index with custom classes • Lab: Debug search issues Perform search reranking with semantic ranking in Azure AI Search • Describe semantic ranking • Set up semantic ranking • Perform semantic ranking on an index • Lab: Use semantic ranking on an index Perform vector search and retrieval in Azure AI Search • Describe vector search • Describe embeddings • Run vector search queries using the REST API • Lab: Use the REST API to run vector search queries