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Implement knowledge mining with Azure AI Search (AI-3022)
Course 8730
1 DAY COURSE

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Course Outline

Unlock insights from structured and unstructured data with Azure AI Search. Learn to extract, analyze, and search your data more effectively by integrating advanced AI capabilities into your applications.

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

  • In this course, you will:

    • Build an Azure AI Search solution to uncover hidden data insights.
    • Implement custom AI skills for enhanced data enrichment.
    • Use knowledge stores to persist enriched data for downstream processes.
    • Enable advanced search features like semantic and vector search.
    • Maintain, optimize, and secure Azure AI Search solutions.

  • Prerequisites

    • Familiarity with Microsoft Azure.
    • Experience in application development using C# or Python.

Azure AI Search Knowledge Mining Training Outline

Learning Objectives

1. Create an Azure AI Search Solution

  • Manage capacity and understand search components.
  • Create and optimize indexes for better data filtering and sorting.
  • Hands-On: Build and test a search solution.

2. Create a Custom Skill for Azure AI Search

  • Add custom AI capabilities like text classification and machine learning skills.
  • Hands-On: Develop a custom skill for enriched data analysis.

3. Create a Knowledge Store with Azure AI Search

  • Learn to persist output from AI enrichment pipelines.
  • Hands-On: Set up a knowledge store for long-term data management.

4. Implement Advanced Search Features

  • Enhance indexes with analyzers, tokenized terms, and multilingual support.
  • Apply term boosting and scoring profiles to improve relevance.
  • Hands-On: Refine search results with advanced techniques.

5. Search Data Outside Azure with Azure Data Factory

  • Index external data using Azure Data Factory and the push API.
  • Hands-On: Add external data to your search indexes.

6. Maintain an Azure AI Search Solution

  • Optimize performance, manage costs, and enhance reliability.
  • Debug issues and monitor solutions effectively.
  • Hands-On: Debug search issues in Azure Portal.

7. Perform Search Reranking with Semantic Ranking

  • Explore L2 semantic ranking and its applications.
  • Hands-On: Use semantic ranking to refine index results.

8. Perform Vector Search and Retrieval

  • Understand vector embeddings and implement vector-based retrieval.
  • Hands-On: Use REST APIs for advanced vector searches.
Course Dates

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Private Team Training

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