Implement knowledge mining with Azure AI Search (AI-3022)

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 Required:
• Familiarity with Microsoft Azure
• Application development experience with C# or Python

Course Outline

1) Create an Azure AI Search solution
• Create an Azure AI Search solution
• Develop a search application
• Lab: Create a search solution

2) 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

3) 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

4) 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

5) 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

6) 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

7) 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

8) 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

9) 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

10) 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