Implement AI Skills in Azure AI Search (AI-3022)

1- Create an Azure AI Search solution

• Create an Azure AI Search solution
• Develop a search application

2- Create a custom skill for Azure AI Search

• Implement a custom skill for Azure AI Search
• Create a custom text classification skill
• Create a machine learning 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

4- 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

5- 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

6- Maintain an Azure AI Search solution

• Familiarity with Microsoft Azure
• Application development experience with C# or Python
• Experience of building a basic search solution with Azure AI Search. If you've not completed the Create an Azure AI Search solution
  module, you should do so before starting this module.

7- Perform search reranking with semantic ranking in Azure AI Search

• Describe semantic ranking
• Set up semantic ranking
• Perform semantic ranking on an index

8- Perform vector search and retrieval in Azure AI Search

• Describe vector search
• Describe embeddings
• Run vector search queries using the REST API
  

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