AI-3022: Implement knowledge mining with Azure AI Search Training

COURSE OVERVIEW

AI-3022: Implement knowledge mining with Azure AI Search

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 AI 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.

Target Audience

AI Engineer
Azure Developer

Prerequisites
Required:

Familiarity with Microsoft Azure
Application development experience with C# or Python

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

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

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Guaranteed to run classes as per your convenient time zone

Industry experienced & certified trainers

Query Handling session by technical expert after 2 month completion of training

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Target Audience

AI Engineer
Azure Developer

Prerequisites
Required:

Familiarity with Microsoft Azure
Application development experience with C# or Python

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

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

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